MASLD/MetALD and mortality in individuals with any cardio-metabolic risk factor: a population based study with 26.7 years of follow-up.

BACKGROUND AIMS: A new term, metabolic dysfunction-associated steatotic liver disease(MASLD), has been proposed by a multi-society expert panel. However, it remains unclear whether hepatic steatosis per se in MASLD contributes to an increased risk of mortality in individuals with any cardio-metabolic risk factor(CMRF), which are also significant risk factors for increased mortality. This study aimed to compare all-cause and cause-specific mortality between the 'MASLD/MetALD' and 'no steatotic liver disease(SLD)' groups in individuals with any CMRF. APPROACH AND RESULTS: A population-based cohort study was conducted using 10,750 participants of NHANES III. All-cause and cause-specific(cardiovascular, cancer, diabetes, and liver) mortality risks were compared between the 'MASLD', 'MetALD', and 'no SLD' groups using the Cox proportional hazards model with complex survey design weights, adjusted for confounders. Over 26 years, the 'MASLD' group did not show significantly increased all-cause(adjusted hazard ratio 1.04[95% confidence interval 0.95-1.14], p=0.413), cardiovascular(0.88[0.75-1.04], p=0.139), or cancer(1.06[0.84-1.33], p=0.635) mortality risk compared to the 'no SLD' group in individuals with any CMRF. The MetALD group was associated with increased all-cause(1.41 [1.05-1.89], p=0.022), cancer(2.35[1.33-4.16], p=0.004) and liver(15.04[2.96-76.35], p=0.002) mortality risk compared with the no SLD group. This trend was more pronounced in MetALD group with advanced fibrosis assessed by FIB-4. CONCLUSION: In individuals with CMRF, the presence of steatotic liver disease (MASLD) alone did not increase the risk of mortality, except in cases with more alcohol consumption (MetALD). Therefore controlling metabolic risk factors and reducing alcohol consumption in people with MASLD or MetALD will be crucial steps to improve long-term health outcomes.

Correlations between heart sound components and hemodynamic variables.

Although the esophageal stethoscope is used for continuous auscultation during general anesthesia, few studies have investigated phonocardiographic data as a continuous hemodynamic index. In this study, we aimed to induce hemodynamic variations and clarify the relationship between the heart sounds and hemodynamic variables through an experimental animal study. Changes in the cardiac contractility and vascular resistance were induced in anesthetized pigs by administering dobutamine, esmolol, phenylephrine, and nicardipine. In addition, a decrease in cardiac output was induced by restricting the venous return by clamping the inferior vena cava (IVC). The relationship between the hemodynamic changes and changes in the heart sound indices was analyzed. Experimental data from eight pigs were analyzed. The mean values of the correlation coefficients of changes in S1 amplitude (ΔS1amp) with systolic blood pressure (ΔSBP), pulse pressure (ΔPP), and ΔdP/dt during dobutamine administration were 0.94, 0.96, and 0.96, respectively. The mean values of the correlation coefficients of ΔS1amp with ΔSBP, ΔPP, and ΔdP/dt during esmolol administration were 0.80, 0.82, and 0.86, respectively. The hemodynamic changes caused by the administration of phenylephrine and nicardipine did not correlate significantly with changes in the heart rate. The S1 amplitude of the heart sound was significantly correlated with the hemodynamic changes caused by the changes in cardiac contractility but not with the variations in the vascular resistance. Heart sounds can potentially provide a non-invasive monitoring method to differentiate the cause of hemodynamic variations.

Optical and UV Shielding Properties of Inorganic Nanoparticles Embedded in Polymethyl Methacrylate Nanocomposite Freestanding Films.

Polymethyl methacrylate (PMMA) is an interesting polymer employed in various applications due to its outstanding properties. However, its electrical and mechanical properties can be further improved by incorporating nanoparticles, and in particular, PMMA nanocomposite with nanoparticles provides various multifunctional properties. This work reports PMMA nanocomposite preparation and structural and optical characterizations incorporating carbon nanotubes (CNTs), TiO2 nanoparticles, and carbon quantum dots (CQDs). CNT/PMMA, TiO2/PMMA, and CQD/PMMA nanocomposite freestanding films were prepared using a simple solution method. Various properties of the prepared composite films were analyzed using scanning electron microscopy, X-ray diffraction, photoluminescence, Fourier transform infrared, and UV-Vis and Raman spectroscopy. Optical parameters and photocatalytic dye degradation for the films are reported, focusing on the properties of the materials. The CNT/PMMA, TiO2/PMMA, and CQD/PMMA films achieved, respectively, good electrical conductivity, photodegradation, and fluorescence compared with other composite films.

CRISPR/Cas9 targeting of passenger single nucleotide variants in haploinsufficient or essential genes expands cancer therapy prospects.

CRISPR/Cas9 technology has effectively targeted cancer-specific oncogenic hotspot mutations or insertion-deletions. However, their limited prevalence in tumors restricts their application. We propose a novel approach targeting passenger single nucleotide variants (SNVs) in haploinsufficient or essential genes to broaden therapeutic options. By disrupting haploinsufficient or essential genes through the cleavage of DNA in the SNV region using CRISPR/Cas9, we achieved the selective elimination of cancer cells without affecting normal cells. We found that, on average, 44.8% of solid cancer patients are eligible for our approach, a substantial increase compared to the 14.4% of patients with CRISPR/Cas9-applicable oncogenic hotspot mutations. Through in vitro and in vivo experiments, we validated our strategy by targeting a passenger mutation in the essential ribosomal gene RRP9 and haploinsufficient gene SMG6. This demonstrates the potential of our strategy to selectively eliminate cancer cells and expand therapeutic opportunities.

Experimental analysis of PM2.5 reduction characteristics between Korean red pine (Pinus densiflora) and sawtooth oak (Quercus acutissima) saplings under different densities and arrangement structures.

As global air pollution, particularly fine particulate matter (PM2.5), has become a major environmental problem, various PM2.5 mitigation technologies including green infrastructure have received significant attention. However, owing to spatial constraints on urban greening, there is a lack of management plans for urban forests to efficiently mitigate PM2.5. In this study, we assessed the PM2.5 reduction capabilities of Pinus densiflora (Korean red pine) and Quercus acutissima (sawtooth oak) by measuring the changes of PM2.5 concentrations using an experimental chamber system. In addition, the PM2.5 reduction efficiency in 90 min (PMRE90) and the amount of PM2.5 reduction per leaf area (PMRLA) were compared based on arrangement structures and density levels. The results showed that the PM2.5 reduction by plants was significantly greater than that of the control experiment without any plants, and an additional reduction effect of approximately 1.38 times was induced by a 1.5 m s-1 air flow. The PMRE90 of Korean red pine was the highest at medium density. In contrast, the PMRE90 of sawtooth oak was the highest at high density. The PMRLA of both species was highest at low densities. The different responses of the species to total reduction were well explained by total leaf area (TLA). The PMRE90 of both species was positively correlated with TLA. The PMRLA of sawtooth oak was approximately 2.3 times greater than that of Korean red pine. However, there were no significant differences in both PMRE90 and PMRLA between the arrangement structures. Our findings reveal the potential mechanisms of vegetation in reducing PM2.5 according to arrangement structure and density. This highlights the importance of efficiently using urban green spaces with spatial constraints on PM2.5 mitigation in the future.

Needle-Free Jet Injection of Poly-(Lactic Acid) for Atrophic Acne Scars: Literature Review and Report of Clinical Cases.

Acne scars, particularly atrophic ones, present a persistent challenge in cosmetic medicine and surgery, requiring extended and multifaceted treatment approaches. Poly-(lactic acid) injectable fillers show promise in managing atrophic acne scars by stimulating collagen synthesis. However, the utilization of needle-free injectors for delivering poly-(lactic acid) into scars remains an area requiring further exploration. In this article, a summary of the latest advancements in needle-free jet injectors is provided, specifically highlighting the variations in jet-producing mechanisms. This summary emphasizes the differences in how these mechanisms operate, offering insights into the evolving technology behind needle-free injection systems. The literature review revealed documented cases focusing on treating atrophic acne scars using intralesional poly-(lactic acid) injections. The results of these clinical studies could be supported by separate in vitro and animal studies, elucidating the feasible pathways through which this treatment operates. However, there is limited information on the use of needle-free jet injectors for the intradermal delivery of poly-(lactic acid). Clinical cases of atrophic acne scar treatment are presented to explore this novel treatment concept, the needle-free delivery of poly-(lactic acid) using a jet pressure-based injector. The treatment demonstrated efficacy with minimal adverse effects, suggesting its potential for scar treatment. The clinical efficacy was supported by histological evidence obtained from cadaver skin, demonstrating an even distribution of injected particles in all layers of the dermis. In conclusion, we suggest that novel needle-free injectors offer advantages in precision and reduce patient discomfort, contributing to scar improvement and skin rejuvenation. Further comprehensive studies are warranted to substantiate these findings and ascertain the efficacy of this approach in scar treatment on a larger scale.

Association between dental diseases and oral hygiene care and the risk of vertebral fracture: a nationwide cohort study.

Periodontal disease and increased missing teeth were associated with incident vertebral fractures. In contrast, professional dental cleaning and frequent tooth brushing, was associated with a lower risk of vertebral fracture. Better oral hygiene care attenuated the risk associated with dental diseases. PURPOSE: To investigate the association between oral health and the risk of vertebral fractures. METHODS: We included 2,532,253 individuals aged ≥40 years who underwent the Korean National Health Insurance Service health examinations in 2008 and followed up until December 31, 2017. We performed multivariable Cox proportional hazard regression analyses to evaluate the association between dental diseases and oral hygiene care and the risk of vertebral fractures. RESULTS: Over the 9.3-year median follow-up, 1.46% (n = 36,857) experienced vertebral fractures. Individuals with dental diseases had a higher risk of vertebral fracture than those without (hazard ratio [HR] 1.04, 95% confidence interval [CI]: 1.02-1.07 for periodontal diseases; 1.02, 1.00-1.05 for dental caries; 1.12, 1.05-1.20 for ≥15 missing teeth). Good oral hygiene care was associated with a lower vertebral fracture risk (HR 0.89, 95% CI: 0.86-0.91 for ≥1 time/year [vs. <1 time/year] of professional dental cleaning; 0.90, 0.87-0.93 for ≥2 times/day [vs. 0-1 time/day] of toothbrushing). The combined dental diseases was significantly associated with an increased vertebral fracture risk, whereas combined oral hygiene care was associated with further risk reduction. Better oral hygiene care reduced vertebral fracture risk associated with dental diseases (all P <0.001). CONCLUSION: Periodontal disease, dental caries, and an increased number of missing teeth were independently associated with higher risks for vertebral fractures. Conversely, improved oral hygiene care, such as personal dental cleaning and frequent tooth brushing, may modify vertebral fracture risks associated with dental disease.

Fabrication of chitosan/fibrin-armored multifunctional silver nanocomposites to improve antibacterial and wound healing activities.

A wound healing substitute promotes rapid tissue regeneration and protects wound sites from microbial contamination. The silver-based antiseptic frequently moist skin stains, burns and irritation, penetrates deep wounds and protects against pathogenic infections. Thus, we formulated a novel fibrin/chitosan encapsulated silver nanoparticle (CH:F:SPG-CH:SNP) composites bandage accelerating the polymicrobial wound healing. Electrospinning method was employed to form the nano-porous, inexpensive, and biocompatible smart bandages. The structural, functional, and mechanical properties were analyzed for the prepared composites. The biological capacity of prepared CH:F:SPG-CH:SNP bandage was assessed against NIH-3 T3 fibroblast and HaCaT cell lines. In vitro hemolytic assays using red blood cells were extensively studied and explored the low hemolytic effect (4.5 %). In addition, the improved drug delivery nature captured for the CH:F:SPG-CH:SNP composite bandage. Antibacterial experiments were achieved against Pseudomonas aeruginosa, Escherichia coli, Staphylococcus aureus and Lactobacillus bulgaricus using zone inhibition method. Moreover, in-vivo wound healing efficacy of fabricated smart bandage was evaluated on the albino Wistar rats which revealed the significant improvement on the postoperative abdomen wounds.

Development of chitosan-based cerium and titanium oxide loaded polycaprolactone for cutaneous wound healing and antibacterial applications.

Cerium dioxide (CeO2) based nanomaterials have emerged as promising dermal equivalents, promoting fibroblast infiltration and tissues regeneration. To enhance the antibacterial and wound healing activity, herein chitosan (CS)-CeO2 combined nano titanium dioxide (TiO2) complex loaded polycaprolactone (PCL) nanohybrid (CS-CeO2/TiO2/PCL) scaffolds were prepared through casting method. The nanohybrid scaffolds' physiochemical, morphological, mechanical, and biological properties were evaluated using advanced analytical techniques. Fourier transform infrared spectroscopy spectrum evidently depicted the various intermolecular interactions on the nanohybrid scaffolds. The developed scaffold exhibited the high swelling behavior and good degradability and permeability which is beneficial for absorbing wound transudation to fasten the healing efficacy. Moreover, CS-CeO2/TiO2/PCL scaffolds owned the better antibacterial activity against bacterial strains E. coli and S. aureus. Also, MTT assay on fibroblast (NIH 3T3) cells and immortalized human keratinocytes (HaCaT) cells indicated improved cell viability and proliferation. In vivo results revealed that the fabricated scaffold full aid to complete wound closure after 14 days which showed CS-CeO2/TiO2/PCL as the significant wound dressing material with potential antibacterial immunity.

Enhancing the performance of premature ventricular contraction detection in unseen datasets through deep learning with denoise and contrast attention module.

Premature ventricular contraction (PVC) is a common and harmless cardiac arrhythmia that can be asymptomatic or cause palpitations and chest pain in rare instances. However, frequent PVCs can lead to more serious arrhythmias, such as atrial fibrillation. Several PVC detection models have been proposed to enable early diagnosis of arrhythmias; however, they lack reliability and generalizability due to the variability of electrocardiograms across different settings and noise levels. Such weaknesses are known to aggravate with new data. Therefore, we present a deep learning model with a novel attention mechanism that can detect PVC accurately, even on unseen electrocardiograms with various noise levels. Our method, called the Denoise and Contrast Attention Module (DCAM), is a two-step process that denoises signals with a convolutional neural network (CNN) in the frequency domain and attends to differences. It focuses on differences in the morphologies and intervals of the remaining beats, mimicking how trained clinicians identify PVCs. Using three different encoder types, we evaluated 1D U-Net with DCAM on six external test datasets. The results showed that DCAM significantly improved the F1-score of PVC detection performance on all six external datasets and enhanced the performance of balancing both the sensitivity and precision of the models, demonstrating its robustness and generalization ability regardless of the encoder type. This demonstrates the need for a trainable denoising process before applying the attention mechanism. Our DCAM could contribute to the development of a reliable algorithm for cardiac arrhythmia detection under real clinical electrocardiograms.

Impact of pH on physicochemical properties of corn starch by dry heat treatment.

This study investigated the effects of temperature, pH, and starch genotype on starch characteristics after dry heat treatment (DHT). DHT starches were prepared according to 19 DHT conditions, constructed using a D-optimal design, and analyzed with respect to apparent amylose (AAM) content, X-ray diffraction (XRD) pattern, relative crystallinity (RC), solubility and swelling power (SP), thermal properties, and pasting viscosity. The DHT starches maintained their granular structures even after DHT at pH 3, although there was some damage to their granular surfaces. The DHT starches showed lower amylose content, RC, SP, gelatinization temperature and enthalpy, degree of retrogradation, and pasting viscosity, but higher solubility, compared to those of native starches. These DHT effects were more pronounced as pH decreased at each temperature, regardless of the starch genotype. Overall, DHT can be used to expand the physical functionality of high-amylose and highly crystallized starches with poor properties. Supplementary Information: The online version contains supplementary material available at 10.1007/s10068-023-01353-7.

Polymer Backbone Stabilized Methylammonium Lead Bromide Perovskite Nano Islands.

Organic-inorganic hybrid perovskite materials continue to attract significant interest due to their optoelectronic application. However, the degradation phenomenon associated with hybrid structures remains a challenging aspect of commercialization. To overcome the stability issue, we have assembled the methylammonium lead bromide nano islands (MNIs) on the backbone of poly-3-dodecyl-thiophene (PDT) for the first time. The structural and morphological properties of the MNI-PDT composite were confirmed with the aid of X-ray diffraction (XRD) studies, Field emission scanning electron microscope (FESEM), and X-ray photoelectron spectroscopy (XPS). The optical properties, namely absorption studies, were carried out by ultraviolet-visible spectroscopy. The fluorescent behavior is determined by photoluminescence (PL) spectroscopy. The emission peak for the MNI-PDT was observed at 536 nm. The morphology studies supported by FESEM indicated that the nano islands are completely covered on the surface of the polymer backbone, making the hybrid (MNI-PDT) stable under environmental conditions for three months. The interfacial interaction strategy developed in the present work will provide a new approach for the stabilization of hybrids for a longer time duration.

Biogenic polymer nanoparticles to remove hydrophobic organic contaminants from water.

Soil and water pollution is of significant concern worldwide because of the consequences of environmental degradation and harmful effects on human health. Water bodies are very much polluted by various organic and inorganic pollutants by different human activities, including industrial wastes. Environmental pollution remains high because of urbanization-induced industrial developments and human lifestyle. It accumulates pollutants in the environment including plants and living organisms. Even mothers' milk is poisoned because of the uncontrolled, widespread increase in pollution. The discharge levels of organic hydrophobic contaminants in the water and soil are increasing rapidly. This severe pollution must be remediated to upgrade the environment and ensure the safety of human beings. It is vital to eradicate soil and water pollution to guarantee sufficient food and water. Different techniques available to remove the pollutants vary according to the type of pollutants. Hydrophobic contaminants are more dangerous than heavy metals and other pollutants; they cannot be easily removed, requiring special care. Hydrophobic organoxenobiotics released in the environment pose severe contamination in soil and water. Therefore, developing efficient and cost-effective processes is necessary to remove hydrophobic contaminants from soil and water. With nanoparticle-mediated remediation techniques, the green-synthesized nanoparticles exhibit improved performance. This review consolidates reports on the remediation techniques of hydrophobic contaminants, focusing on green-synthesized remediation agents. The very limited works on green synthesis of polymeric nanoparticles, particularly polyurethane-based materials for organic contaminants removal demand more attention in this area. PRACTITIONER POINTS: Consolidated the effects of hydrophobic organic and plastic contaminants on environment degradation. Summarized the advantages of green synthesized polymer nanoparticles for efficient removal of hydrophobic contaminants. Discussed the different sources of pollution and remediation techniques referring 112 research works.

GS-DeepNet: mastering tokamak plasma equilibria with deep neural networks and the Grad-Shafranov equation.

The force-balanced state of magnetically confined plasmas heated up to 100 million degrees Celsius must be sustained long enough to achieve a burning-plasma state, such as in the case of ITER, a fusion reactor that promises a net energy gain. This force balance between the Lorentz force and the pressure gradient force, known as a plasma equilibrium, can be theoretically portrayed together with Maxwell's equations as plasmas are collections of charged particles. Nevertheless, identifying the plasma equilibrium in real time is challenging owing to its free-boundary and ill-posed conditions, which conventionally involves iterative numerical approach with a certain degree of subjective human decisions such as including or excluding certain magnetic measurements to achieve numerical convergence on the solution as well as to avoid unphysical solutions. Here, we introduce GS-DeepNet, which learns plasma equilibria through solely unsupervised learning, without using traditional numerical algorithms. GS-DeepNet includes two neural networks and teaches itself. One neural network generates a possible candidate of an equilibrium following Maxwell's equations and is taught by the other network satisfying the force balance under the equilibrium. Measurements constrain both networks. Our GS-DeepNet achieves reliable equilibria with uncertainties in contrast with existing methods, leading to possible better control of fusion-grade plasmas.

Discovery of a novel NAMPT inhibitor that selectively targets NAPRT-deficient EMT-subtype cancer cells and alleviates chemotherapy-induced peripheral neuropathy.

Background: Exploiting synthetic lethality (SL) relationships between protein pairs has emerged as an important avenue for the development of anti-cancer drugs. Nicotinamide phosphoribosyltransferase (NAMPT) is the rate-limiting enzyme of the NAD+ salvage pathway, having an SL relationship with nicotinic acid phosphoribosyltransferase (NAPRT), the key enzyme in the NAD+ Preiss-Handler pathway. NAMPT inhibitor holds clinical potential not only as a promising cancer treatment but also as a means of protection against chemotherapy-induced-peripheral-neuropathy (CIPN). However, as NAD+ is essential for normal cells, the clinical use of NAMPT inhibitors is challenging. This study aimed to identify a novel NAMPT inhibitor with enhanced selective cytotoxicity against NAPRT-deficient cancer cells as well as prominent efficacy in alleviating CIPN. Methods: We began by conducting drug derivatives screening in a panel of lung cancer cell lines to select an agent with the broadest therapeutic window between the NAPRT-negative and-positive cancer cell lines. Both in vitro and In vivo comparative analyses were conducted between A4276 and other NAMPT inhibitors to evaluate the NAPRT-negative cancer cell selectivity and the underlying distinct NAMPT inhibition mechanism of A4276. Patient-derived tumor transcriptomic data and protein levels in various cancer cell lines were analyzed to confirm the correlation between NAPRT depletion and epithelial-to-mesenchymal transition (EMT)-like features in various cancer types. Finally, the efficacy of A4276 for axonal protection and CIPN remedy was examined in vitro and in vivo. Results: The biomarker-driven phenotypic screening led to a discovery of A4276 with prominent selectivity against NAPRT-negative cancer cells compared with NAPRT-positive cancer cells and normal cells. The cytotoxic effect of A4276 on NAPRT-negative cells is achieved through its direct binding to NAMPT, inhibiting its enzymatic function at an optimal and balanced level allowing NAPRT-positive cells to survive through NAPRT-dependent NAD+ synthesis. NAPRT deficiency serves as a biomarker for the response to A4276 as well as an indicator of EMT-subtype cancer in various tumor types. Notably, A4276 protects axons from Wallerian degeneration more effectively than other NAMPT inhibitors by decreasing NMN-to-NAD+ ratio. Conclusion: This study demonstrates that A4276 selectively targets NAPRT-deficient EMT-subtype cancer cells and prevents chemotherapy-induced peripheral neuropathy, highlighting its potential as a promising anti-cancer agent for use in cancer monotherapy or combination therapy with conventional chemotherapeutics.

Fabrication of Ru loaded MgB2 with guar gum hybrid for photocatalytic degradation of crystal violet.

Today, dyes/pigment-based materials are confronting a serious issue in harming marine ecology. Annihilate these serious water pollutants using photoactive 2D nanohybrid catalysts showed promising comparativeness over available photocatalysts. In the present work, a facile route to decorate Ruthenium (Ru) on 2D MgB2 flower-like nanostructures was developed via ecofriendly guar gum biopolymer substantial template (MgB2/GG@Ru NFS) and its photocatalytic performance was reported. Synthesis of MgB2@Ru, MgB2/GG@Ru NFS and commercial MgB2, was studied by FTIR, XRD, FE-SEM, EDX, AFM, TEM, UV-vis spectra, and XPS analysis. From the results, the MgB2/GG@Ru NFS exhibited a superior photocatalytic performance (99.7 %) than its precursors MgB2@Ru (79.7 %), and MgB2 (53.7 %), with the degradation efficiency of the crystal violet (CV) within 100 min under visible light irradiation. The proposed photo-catalyst MgB2/GG@Ru NFS showed negligible loss of photocatalytic activity even after five successive cycles, revealing its reusability and enhanced stability due to the network structure. The photocatalytic mechanism for MgB2/GG@Ru NFS was evaluated by trapping experiment of active species, verifying that superoxide (O2-) and electron (e-) contributed significant role in the dye degradation.

Development of a Bispectral index score prediction model based on an interpretable deep learning algorithm.

BACKGROUND: Proper maintenance of hypnosis is crucial for ensuring the safety of patients undergoing surgery. Accordingly, indicators, such as the Bispectral index (BIS), have been developed to monitor hypnotic levels. However, the black-box nature of the algorithm coupled with the hardware makes it challenging to understand the underlying mechanisms of the algorithms and integrate them with other monitoring systems, thereby limiting their use. OBJECTIVE: We propose an interpretable deep learning model that forecasts BIS values 25 s in advance using 30 s electroencephalogram (EEG) data. MATERIAL AND METHODS: The proposed model utilized EEG data as a predictor, which is then decomposed into amplitude and phase components using fast Fourier Transform. An attention mechanism was applied to interpret the importance of these components in predicting BIS. The predictability of the model was evaluated on both regression and binary classification tasks, where the former involved predicting a continuous BIS value, and the latter involved classifying a dichotomous status at a BIS value of 60. To evaluate the interpretability of the model, we analyzed the attention values expressed in the amplitude and phase components according to five ranges of BIS values. The proposed model was trained and evaluated using datasets collected from two separate medical institutions. RESULTS AND CONCLUSION: The proposed model achieved excellent performance on both the internal and external validation datasets. The model achieved a root-mean-square error of 6.614 for the regression task, and an area under the receiver operating characteristic curve of 0.937 for the binary classification task. Interpretability analysis provided insight into the relationship between EEG frequency components and BIS values. Specifically, the attention mechanism revealed that higher BIS values were associated with increased amplitude attention values in high-frequency bands and increased phase attention values in various frequency bands. This finding is expected to facilitate a more profound understanding of the BIS prediction mechanism, thereby contributing to the advancement of anesthesia technologies.

Self-Assembly of Copper Oxide Interfaced MnO2 for Oxygen Evolution Reaction.

Designing efficient electrocatalytic systems through facile synthesis remains a formidable task. To address this issue, this paper presents the design of a combination material comprising two transition metal oxides (copper oxide and manganese oxide (CuO/MnO2)), synthesized using a conventional microwave technique to efficiently engage as an active oxygen evolution reaction (OER) catalyst. The structural and morphological properties of the composite were confirmed by the aid of X-ray diffraction (XRD) studies, field emission scanning electron microscopy (FESEM), X-ray photoelectron spectroscopy (XPS), and energy-dispersive spectrometry (EDS). FESEM clearly indicated well-aligned interlacing of CuO with MnO2. The OER performance was carried out in 1 M KOH. The assembled CuO/MnO2 delivered a benchmark current density (j = 10 mA cm-2) at a minimal overpotential (η = 294 mV), while pristine CuO required a high η (316 mV). Additionally, the CuO/MnO2 electrocatalyst exhibited stability for more than 15 h. These enhanced electrochemical performances were attributed to the large volume and expanded diameter of the pores, which offer ample surface area for catalytic reactions to boost OER. Furthermore, the rate kinetics of the OER are favored in composite due to low Tafel slope (77 mV/dec) compared to CuO (80 mV/dec).

Room-temperature response of MOF-derived Pd@PdO core shell/γ-Fe2O3 microcubes decorated graphitic carbon based ultrasensitive and highly selective H2 gas sensor.

With the current upsurge in hydrogen economies all over the world, an increased demand for improved chemiresistive H2 sensors that are highly responsive and fast acting when exposed to gases is expected. Owing to safety concerns about explosive and highly flammable H2 gas, it is important to develop resistive sensors that can detect the leakage of H2 gas swiftly and selectively. Currently, interest in metal-organic frameworks (MOFs) for gas-sensor applications is increasing due to their open-metal sites, large surface area, and unique surface morphologies. In this research, a highly selective and sensitive H2-sensor was established based on graphitic carbon (GC) anchored spherical Pd@PdO core-shells over γ-Fe2O3 microcube (Pd@PdO/γ-Fe2O3@GC which is termed as S3) heterostructure materials. The combined solvothermal followed by controlled calcination-assisted S3 exhibited a specific morphology with the highest surface area of 79.12 m2 g-1, resulting in fast response and recovery times (21 and 29 s, respectively), and excellent sensing performance (ΔR/R0∼ 96.2 ± 1.5), outstanding long-term stability, and a 100 ppb detection limit when detecting H2-gas at room temperature (mainly in very humid surroundings). This result proves that adsorption sites provided by S3 can promote surface reactions (adsorption and desorption) for ultrasensitive and selective H2gas sensors.

Comparisons of PM2.5 mitigation with stand characteristics between evergreen Korean pine plantations and deciduous broad-leaved forests in the Republic of Korea.

Owing to industrialization and urbanization in recent decades, fine particulate matter (PM2.5) in the atmosphere has become a major environmental problem worldwide. This environmental issue pushed the use of forests as air filtering tools. However, there is a lack of continuous and long-term forest management to efficiently mitigate PM2.5. In this study, we assessed the potential of different forest types to control air pollution by measuring the seasonal PM2.5 concentrations inside and outside the forest for one year. In addition, the PM2.5 reduction efficiencies (PMREs) of two forest types were compared, and their relationship with stand characteristics was analyzed. The results showed that the average PMRE inside the forests was approximately 18.2%; the seasonal PMRE was highest in winter (approximately 28.1%) and lowest in summer (approximately 9.6%). The average PMRE of the Taehwa deciduous broad-leaved forest (TDF) (approximately 18.8%) was significantly higher than that of the Taehwa coniferous forest (TCF) (approximately 17.5%) (P < 0.001); differences were also observed seasonally. The PMRE in the TCF was higher in spring and summer (P < 0.001), while that in the TDF was higher in autumn and winter (P < 0.001). Furthermore, the PMRE in the TDF was negatively correlated with stand density (P = 0.003) and positively correlated with the average diameter at breast height (DBH) (P = 0.028). However, the PMRE in the TCF did not significantly correlate with stand characteristics. As such, the results of this study revealed the differences in PM2.5 mitigation according to stand characteristics, which should be considered in urban forest management.