Association Between Atrial Fibrillation Symptoms and Clinical Outcomes: A Prospective Multicenter Registry Study.

The presence of symptoms plays an important role in determining whether to focus on rhythm control or rate control when treating atrial fibrillation (AF). Previous comparative studies on the clinical outcomes of symptomatic and asymptomatic AF have yielded inconsistent results, and a link between AF symptoms and left atrial (LA) remodeling is not established. Patients selected from the COmparison study of Drugs for symptom control and complication prEvention of AF (CODE-AF) registry, which is a prospective, multicenter study consisting of patients with non-valvular AF, were grouped into 2 groups: symptomatic and asymptomatic. The primary outcome was a composite of the following cardiovascular outcomes: all-cause death, ischemic stroke, transient ischemic attack, systemic embolism, myocardial infarction, and heart failure hospitalization. Of 10,210 patients with AF, 4,327 (42%) had symptomatic AF. The asymptomatic group had an older mean age, more men, and more patients with hypertension and diabetes mellitus than the symptomatic group. The asymptomatic group had a larger left atrium (LA) diameter (43.6 vs 42.2 mm, p <0.001) than the symptomatic group. During a median follow-up of 32.9 (29.5 to 36.4) months, the asymptomatic and symptomatic groups showed similar incidences of the primary outcome (1.44 vs 1.45 per 100 person-years; log-rank, p = 0.8). In conclusion, the absence of AF symptoms is associated with increased LA. However, symptomatic and asymptomatic patients with AF have a similar risk of cardiovascular outcomes. This suggests that beneficial treatment for AF may be considered regardless of whether patients have symptomatic or asymptomatic AF.

Single-Nucleotide Microbial Genome Editing Using CRISPR-Cas12a.

Microbial genome editing can be achieved by donor DNA-directed mutagenesis and CRISPR-Cas12a-mediated negative selection. Single-nucleotide-level genome editing enables the manipulation of microbial cells exactly as designed. Here, we describe single-nucleotide substitutions/indels in the target DNA of E. coli genome using a mutagenic DNA oligonucleotide donor and truncated crRNA/Cas12a system. The maximal truncation of nucleotides at the 3'-end of the crRNA enables Cas12a-mediated single-nucleotide-level precise editing at galK targets in the genome of E. coli.

Corrigendum: Korean Ginseng Berry Extract Enhances the Male Steroidogenesis Enzymes In Vitro and In Vivo.

This corrects the article on p. 446 in vol. 41, PMID: 36649918.

Production of safe cyanobacterial biomass for animal feed using wastewater and drinking water treatment residuals.

The growing interest in microalgae and cyanobacteria biomass as an alternative to traditional animal feed is hindered by high production costs. Using wastewater (WW) as a cultivation medium could offer a solution, but this approach risks introducing harmful substances into the biomass, leading to significant safety concerns. In this study, we addressed these challenges by selectively extracting nitrates and phosphates from WW using drinking water treatment residuals (DWTR) and chitosan. This method achieved peak adsorption capacities of 4.4 mg/g for nitrate and 6.1 mg/g for phosphate with a 2.5 wt% chitosan blend combined with DWTR-nitrogen. Subsequently, these extracted nutrients were employed to cultivate Spirulina platensis, yielding a biomass productivity rate of 0.15 g/L/d, which is comparable to rates achieved with commercial nutrients. By substituting commercial nutrients with nitrate and phosphate from WW, we can achieve a 18 % reduction in the culture medium cost. While the cultivated biomass was initially nitrogen-deficient due to low nitrate levels, it proved to be protein-rich, accounting for 50 % of its dry weight, and contained a high concentration of free amino acids (1260 mg/g), encompassing all essential amino acids. Both in vitro and in vivo toxicity tests affirmed the biomass's safety for use as an animal feed component. Future research should aim to enhance the economic feasibility of this alternative feed source by developing efficient adsorbents, utilizing cost-effective reagents, and implementing nutrient reuse strategies in spent mediums.

Effect of multiple quantum well periods on structural properties and performance of extended short-wavelength infrared LEDs.

We present research on the role of multiple quantum well periods in extended short-wavelength infrared InGaAs/InAsPSb type-I LEDs. The fabricated LEDs consisted of 6, 15, and 30 quantum well periods, and we evaluated the structural properties and device performance through a combination of theoretical simulations and experimental characterization. The strain and energy band offset was precisely controlled by carefully adjusting the composition of the InAsPSb quaternary material, achieving high valence and conduction band offsets of 350 meV and 94 meV, respectively. Our LEDs demonstrated a high degree of relaxation of 94-96 %. Additionally, we discovered that the temperature-dependent dark current characterization attributed to generation-recombination and trap-assign tunneling, with trap-assign tunneling being more dominant at lower current injections. Electroluminescence analysis revealed that the predominant emission mechanism of the LEDs originated from localized exciton and free exciton radiative recombination, which the 30 quantum wells LED exhibited the highest contribution of the localized exciton/free exciton radiative recombination. We observed that increasing the quantum well periods from 6 to 15 led to an increase in the 300 K electroluminescence intensity of the LED. However, extending the quantum well period to 30 resulted in a decline in emission intensity due to the degradation of the epitaxial film quality.

Monocular Depth Estimation from a Fisheye Camera Based on Knowledge Distillation.

Monocular depth estimation is a task aimed at predicting pixel-level distances from a single RGB image. This task holds significance in various applications including autonomous driving and robotics. In particular, the recognition of surrounding environments is important to avoid collisions during autonomous parking. Fisheye cameras are adequate to acquire visual information from a wide field of view, reducing blind spots and preventing potential collisions. While there have been increasing demands for fisheye cameras in visual-recognition systems, existing research on depth estimation has primarily focused on pinhole camera images. Moreover, depth estimation from fisheye images poses additional challenges due to strong distortion and the lack of public datasets. In this work, we propose a novel underground parking lot dataset called JBNU-Depth360, which consists of fisheye camera images and their corresponding LiDAR projections. Our proposed dataset was composed of 4221 pairs of fisheye images and their corresponding LiDAR point clouds, which were obtained from six driving sequences. Furthermore, we employed a knowledge-distillation technique to improve the performance of the state-of-the-art depth-estimation models. The teacher-student learning framework allows the neural network to leverage the information in dense depth predictions and sparse LiDAR projections. Experiments were conducted on the KITTI-360 and JBNU-Depth360 datasets for analyzing the performance of existing depth-estimation models on fisheye camera images. By utilizing the self-distillation technique, the AbsRel and SILog error metrics were reduced by 1.81% and 1.55% on the JBNU-Depth360 dataset. The experimental results demonstrated that the self-distillation technique is beneficial to improve the performance of depth-estimation models.

Quantum Diamonds at the Beach: Chemical Insights into Silica Growth on Nanoscale Diamond using Multimodal Characterization and Simulation.

Surface chemistry of materials that host quantum bits such as diamond is an important avenue of exploration as quantum computation and quantum sensing platforms mature. Interfacing diamond in general and nanoscale diamond (ND) in particular with silica is a potential route to integrate room temperature quantum bits into photonic devices, fiber optics, cells, or tissues with flexible functionalization chemistry. While silica growth on ND cores has been used successfully for quantum sensing and biolabeling, the surface mechanism to initiate growth was unknown. This report describes the surface chemistry responsible for silica bond formation on diamond and uses X-ray absorption spectroscopy (XAS) to probe the diamond surface chemistry and its electronic structure with increasing silica thickness. A modified Stöber (Cigler) method was used to synthesize 2-35 nm thick shells of SiO2 onto carboxylic acid-rich ND cores. The diamond morphology, surface, and electronic structure were characterized by overlapping techniques including electron microscopy. Importantly, we discovered that SiO2 growth on carboxylated NDs eliminates the presence of carboxylic acids and that basic ethanolic solutions convert the ND surface to an alcohol-rich surface prior to silica growth. The data supports a mechanism that alcohols on the ND surface generate silyl-ether (ND-O-Si-(OH)3) bonds due to rehydroxylation by ammonium hydroxide in ethanol. The suppression of the diamond electronic structure as a function of SiO2 thickness was observed for the first time, and a maximum probing depth of ∼14 nm was calculated. XAS spectra based on the Auger electron escape depth was modeled using the NIST database for the Simulation of Electron Spectra for Surface Analysis (SESSA) to support our experimental results. Additionally, resonant inelastic X-ray scattering (RIXS) maps produced by the transition edge sensor reinforces the chemical analysis provided by XAS. Researchers using diamond or high-pressure high temperature (HPHT) NDs and other exotic materials (e.g., silicon carbide or cubic-boron nitride) for quantum sensing applications may exploit these results to design new layered or core-shell quantum sensors by forming covalent bonds via surface alcohol groups.

Knowledge distillation of multi-scale dense prediction transformer for self-supervised depth estimation.

Depth estimation is an inverse projection problem that estimates pixel-level distances from a single image. Although, supervised methods have shown promising results, it has intrinsic limitations in requiring ground truth depth from an external sensor. On the other hand, self-supervised depth estimation relieves the burden for collecting calibrated training data, while there is still a large performance gap between supervised and self-supervised methods. The objective of this study is to reduce the performance gap between the supervised and self-supervised approaches. The loss function of previous self-supervised methods is mainly based on a photometric error, which is indirectly computed from synthesized images using depth and pose estimates. In this paper, we argue that direct depth cue is more effective to train a depth estimation network. To obtain the direct depth cue, we employed a knowledge distillation technique, which is a teacher-student learning framework. The teacher network was trained in a self-supervised manner based on a photometric error, and its predictions were utilized to train a student network. We constructed a multi-scale dense prediction transformer with Monte Carlo dropout, and multi-scale distillation loss was proposed to train the student network based on the ensemble of stochastic estimates. Experiments were conducted on the KITTI and Make3D datasets, and our proposed method achieved the state-of-the-art accuracy in self-supervised depth estimation. Our code is publicly available at https://github.com/ji-min-song/KD-of-MS-DPT .

Skin rejuvenating effect of a combined triple-wavelength (755 nm, 810 nm, and 1064 nm) laser: a preliminary study.

With an increasing demand for noninvasive skin rejuvenation techniques, several light-based devices have been introduced. Due to its ability to deliver thermal energy from the superficial to deeper levels of the dermis, a combined triple-wavelength laser (755 nm, 810 nm, and 1064 nm) can be used for skin rejuvenation. The objective of this study was to assess the effectiveness and safety of a combined triple-wavelength laser for skin rejuvenation. A total of 28 female patients seeking skin rejuvenation treatment were included. All patients underwent five consecutive treatment sessions at a two-week interval. Clinical improvement of aging-related cutaneous change was noted by the treating dermatologists and patients. Biopsies were performed on the faces of consenting patients before and two weeks after the final treatment. Significant clinical improvements were observed by both patients and evaluating dermatologists. Based on the patient satisfaction questionnaire, 78% of patients reported a self-assessed improvement of more than 25%. Additionally, 86% of patients showed an improvement of more than 25% on objective assessment by dermatologists. Histopathological findings revealed increased collagen and elastic bundles throughout the dermis. Except for transient pain during treatment, no serious adverse effects were reported. The findings of this study suggest that the combined triple-wavelength laser may be an effective and safe nonablative option for skin rejuvenation.

A deep learning model for automated kidney calculi detection on non-contrast computed tomography scans in dogs.

Nephrolithiasis is one of the most common urinary disorders in dogs. Although a majority of kidney calculi are non-obstructive and are likely to be asymptomatic, they can lead to parenchymal loss and obstruction as they progress. Thus, early diagnosis of kidney calculi is important for patient monitoring and better prognosis. However, detecting kidney calculi and monitoring changes in the sizes of the calculi from computed tomography (CT) images is time-consuming for clinicians. This study, in a first of its kind, aims to develop a deep learning model for automatic kidney calculi detection using pre-contrast CT images of dogs. A total of 34,655 transverseimage slices obtained from 76 dogs with kidney calculi were used to develop the deep learning model. Because of the differences in kidney location and calculi sizes in dogs compared to humans, several processing methods were used. The first stage of the models, based on the Attention U-Net (AttUNet), was designed to detect the kidney for the coarse feature map. Five different models-AttUNet, UTNet, TransUNet, SwinUNet, and RBCANet-were used in the second stage to detect the calculi in the kidneys, and the performance of the models was evaluated. Compared with a previously developed model, all the models developed in this study yielded better dice similarity coefficients (DSCs) for the automatic segmentation of the kidney. To detect kidney calculi, RBCANet and SwinUNet yielded the best DSC, which was 0.74. In conclusion, the deep learning model developed in this study can be useful for the automated detection of kidney calculi.

Transcriptomic analysis of the antimicrobial activity of prodigiosin against Cutibacterium acnes.

Prodigiosin, a red pigment produced by Hahella chejuensis, a marine-derived microorganism, has several biological functions, including antimicrobial activity and inflammatory relief. In this study, the antibacterial activity of prodigiosin against skin microorganisms was explored. Paper disc assay on skin bacterial cells revealed that Cutibacterium acnes related to acne vulgaris highly susceptible to prodigiosin. MIC (Minimal Inhibitory Concentration) and MBC (Minimal Bactericidal Concentration) were determined on Cutibacterium species. The RNA-seq analysis of prodigiosin-treated C. acnes cells was performed to understand the antibacterial mechanism of prodigiosin. Among changes in the expression of hundreds of genes, the expression of a stress-responsive sigma factor encoded by sigB increased. Conversely, the gene expression of cell wall biosynthesis and energy metabolism was inhibited by prodigiosin. Specifically, the expression of genes related to the metabolism of porphyrin, a pro-inflammatory metabolite, was significantly reduced. Therefore, prodigiosin could be used to control C. acnes. Our study provided new insights into the antimicrobial mechanism of prodigiosin against C. acnes strains.

Risk of Subsequent Primary Cancer in Thyroid Cancer Survivors: A Nationwide Population-Based Study.

Background: Despite obtaining a good prognosis and long life expectancy, survivors of thyroid cancer can nevertheless develop subsequent primary cancer (SPC). We investigated the risk and types of SPC in patients with thyroid cancer and compared them with subjects without thyroid cancer history (controls). Methods: We conducted a nationwide, population-based, retrospective cohort study based on the Korean National Health Insurance Database. A total of 432,654 patients diagnosed with thyroid cancer between 2004 and 2019 were 1:1 matched with controls for age, sex, income, and region of residence. The hazard ratios (HR) and 95% confidence intervals (CI) of SPC were estimated using Cox proportional hazard models. Results: In total, 78,584 (18.2%) patients with thyroid cancer and 49,979 (11.6%) controls were diagnosed with SPCs over a mean follow-up of 6.9 years. Patients with thyroid cancer had a higher risk of SPC at any site (adjusted HR, 1.62; 95% CI, 1.60-1.64) than the controls. The risk of SPCs was particularly high for patients diagnosed with thyroid cancer at a younger age (<40 years) and within 5 years. Conclusions: Medical caregivers should consider the long-term follow-up of patients with thyroid cancer and discuss the risk of SPC, especially if they complain of cancer-related symptoms.

Changes in the mean incidence and variance of orthopedic diseases before and during the COVID-19 pandemic in Korea: a retrospective study.

BACKGROUND: During the coronavirus disease (COVID-19) pandemic, the amount of moderate- to high-intensity physical activity significantly decreased. Therefore, the epidemiology of musculoskeletal diseases could possibly have changed. We assessed changes in the incidence of and variance in non-traumatic orthopedic diseases before and after the COVID-19 pandemic in Korea. METHODS: This study included data from the Korea National Health Insurance Service, which covers the entire Korean population (approximately 50 million), from January 2018 to June 2021. Using International Classification of Diseases, Tenth Revision codes, 12 common orthopedic diseases were evaluated, including cervical disc disorders, lumbar disc disorders, forward head posture, myofascial pain syndrome, carpal tunnel syndrome, tennis elbow, frozen shoulder, rheumatoid arthritis, gout, hip fracture, distal radius fracture, and spine fracture diseases. "Pre-COVID-19" was the period until February 2020, and "COVID-19 pandemic period" was the period starting March 2020. Differences in the mean incidence and variance of diseases before and during the COVID-19 pandemic were compared. RESULTS: In most cases, the incidence of orthopedic diseases decreased at the beginning of the pandemic and then increased thereafter. Among the 12 diseases, the incidence of three diseases showed a statistically significant change. The incidence of myofascial pain syndrome (P < 0.001) was lower during the COVID-19 pandemic than during the pre-COVID-19 period. The incidences of frozen shoulder (P < 0.001) and gout (P = 0.043) were higher during the COVID-19 pandemic than during the pre-COVID-19 period. However, no statistical difference in disease variations was observed between the two periods. CONCLUSIONS: The incidence of orthopedic diseases varied during the COVID-19 pandemic among the Korean population. Although the incidence of myofascial pain syndrome was lower, that of frozen shoulder and gout was higher during the COVID-19 pandemic than during the pre-COVID-19 period. No disease variations during the COVID-19 pandemic were found.

Inorganic-Organic Double Network Ionogels Based on Silica Nanoparticles for High-Temperature Flexible Supercapacitors.

Herein, we demonstrate an inorganic-organic double network gel electrolyte consisting of a silica particle network and a poly-2-hydroxyethyl methacrylate network in which 1-butyl-3-methylimidazolium tetrafluoroborate ionic liquids are confined. The as-synthesized double network ionogel electrolytes exhibited high ion conductivity of 3.8 to 12.8 mS cm-1 over a wide temperature range of 30 to 150 °C and mechanical integrity with a maximum toughness of 1.8 MJ m-3 at 30 °C. These remarkable properties of the ionogel were associated with the formation of an optimal physical network of the silica nanoparticles in the colloidal dispersion. Accordingly, a flexible supercapacitor using ionogel electrolytes and reduced graphene oxide electrodes delivered energy and power densities of 48 Wh kg-1 and 4 kW kg-1, respectively, even at a high temperature of 120 °C, demonstrating excellent long-term stability that retains 93% of the initial capacitance even over 10,000 charge/discharge cycles at 120 °C.

Exercise Frequency Reduction Is Associated With Higher Risk of Infection in Newly Diagnosed Diabetes: A Nationally Representative Cohort Study.

BACKGROUND: Exercise is an important method to control the progression of diabetes. Since diabetes compromises immune function and increases the risk of infectious diseases, we hypothesized that exercise may affect the risk of infection by its immunoprotective effects. However, population-based cohort studies regarding the association between exercise and the risk of infection are limited, especially regarding changes in exercise frequency. The aim of this study was to determine the association between the change in exercise frequency and the risk of infection among patients with newly diagnosed diabetes. METHODS: Data of 10,023 patients with newly diagnosed diabetes were extracted from the Korean National Health Insurance Service-Health Screening Cohort. Self-reported questionnaires for moderate-to-vigorous physical activity (MVPA) were used to classify changes in exercise frequency between two consecutive two-year periods of health screenings (2009-2010 and 2011-2012). The association between changes in exercise frequency and the risk of infection was evaluated using multivariable Cox proportional-hazards regression. RESULTS: Compared with engaging in ≥ 5 times of MVPA/week during both periods, a radical decrease in MVPA (from ≥ 5 times of MVPA/week to physical inactivity) was associated with a higher risk of pneumonia (adjusted hazard ratio [aHR], 1.60; 95% confidence interval [CI], 1.03-2.48) and upper respiratory tract infection (aHR, 1.15; 95% CI, 1.01-1.31). In addition, a reduction of MVPA from ≥ 5 to < 5 times of MVPA/week was associated with a higher risk of pneumonia (aHR, 1.52; 95% CI, 1.02-2.27), whereas the risk of upper respiratory tract infection was not higher. CONCLUSION: Among patients with newly diagnosed diabetes, a reduction in exercise frequency was related to an increase in the risk of pneumonia. For patients with diabetes, a modest level of physical activity may need to be maintained to reduce the risk of pneumonia.

Multiplex Single-Nucleotide Microbial Genome Editing Achieved by CRISPR-Cas9 Using 5'-End-Truncated sgRNAs.

Multiplex genome editing with CRISPR-Cas9 offers a cost-effective solution for time and labor savings. However, achieving high accuracy remains a challenge. In an Escherichia coli model system, we achieved highly efficient single-nucleotide level simultaneous editing of the galK and xylB genes using the 5'-end-truncated single-molecular guide RNA (sgRNA) method. Furthermore, we successfully demonstrated the simultaneous editing of three genes (galK, xylB, and srlD) at single-nucleotide resolution. To showcase practical application, we targeted the cI857 and ilvG genes in the genome of E. coli. While untruncated sgRNAs failed to produce any edited cells, the use of truncated sgRNAs allowed us to achieve simultaneous and accurate editing of these two genes with an efficiency of 30%. This enabled the edited cells to retain their lysogenic state at 42 °C and effectively alleviated l-valine toxicity. These results suggest that our truncated sgRNA method holds significant potential for widespread and practical use in synthetic biology.

Regulating Cation Interactions for Zero-Strain and High-Voltage P2-type Na2/3 Li1/6 Co1/6 Mn2/3 O2 Layered Oxide Cathodes of Sodium-Ion Batteries.

Deep sodium extraction/insertion of sodium cathodes usually causes undesired Jahn-Teller distortion and phase transition, both of which will reduce structural stability and lead to poor long-cycle reliability. Here we report a zero-strain P2- Na2/3 Li1/6 Co1/6 Mn2/3 O2 cathode, in which the lithium/cobalt substitution contributes to reinforcing the host structure by reducing the Mn3+ /Mn4+ redox, mitigating the Jahn-Teller distortion, and minimizing the lattice change. 94.5 % of Na+ in the unit structure can be reversibly cycled with a charge cut-off voltage of 4.5 V (vs. Na+ /Na). Impressively, a solid-solution reaction without phase transitions is realized upon deep sodium (de)intercalation, which poses a minimal volume deviation of 0.53 %. It attains a high discharge capacity of 178 mAh g-1 , a high energy density of 534 Wh kg-1 , and excellent capacity retention of 95.8 % at 1 C after 250 cycles.

Inverse association between changes in systolic and diastolic blood pressure and risk of depression: A nationally representative cohort study.

BACKGROUND: Depression is one of complex mental disorders with diverse etiological factors but the association between blood pressure (BP) and depression is unknown. We aimed to investigate the association between changes in BP (systolic and diastolic) and incident depression. METHODS: From the National Health Insurance Service-Health Screening Cohort (NHIS-HEALS), 224,192 participants who underwent biennial health screenings from period I (2004-05) and II (2006-07) were included in the study. Systolic BP (SBP) and diastolic BP (DBP) categories were defined as follows: SBP into 5 categories (<90 mmHg, 90 mmHg -119 mmHg, 120 mmHg -129 mmHg, 130 mmHg -139 mmHg, ≥140 mmHg) and DBP into 4 categories (<60 mmHg, 60 mmHg -79 mmHg, 80 mmHg -89 mmHg, ≥90 mmHg). Also, BP levels were classified into 5 groups: normal, elevated BP, stage 1 BP, stage 2 BP, hypotension. Using the Cox proportional hazards regression, changes in SBP and DBP between two screening periods and the risk of depression were calculated by adjusted hazard ratio (aHR) and 95 % confidence interval (CI). RESULTS: There were 17,780 depression events during 1.5 million person-year of follow-up. Compared to the participants with SBP ≥ 140 mmHg or DBP ≥ 90 mmHg from both periods, those who decreased SBP from ≥140 mmHg to 120 mmHg-129 mmHg (aHR 1.13; 95 % CI 1.04-1.24; P = 0.001) and those who decreased DBP from ≥90 mmHg to 60 mmHg-79 mmHg (aHR 1.10; 95 % CI 1.02-1.20; P = 0.020) showed a higher risk of depression, respectively. CONCLUSIONS: Changes in SBP and DBP showed an inverse relationship with depression risk.

Enhanced Results on Sampled-Data Synchronization for Chaotic Neural Networks With Actuator Saturation Using Parameterized Control.

This article investigates a novel sampled-data synchronization controller design method for chaotic neural networks (CNNs) with actuator saturation. The proposed method is based on a parameterization approach which reformulates the activation function as the weighted sum of matrices with the weighting functions. Also, controller gain matrices are combined by affinely transformed weighting functions. The enhanced stabilization criterion is formulated in terms of linear matrix inequalities (LMIs) based on the Lyapunov stability theory and weighting function's information. As shown in the comparison results of the bench marking example, the presented method much outperforms previous methods, and thus the enhancement of the proposed parameterized control is verified.