Internal quality prediction technology for 'Sulhyang' strawberry fruit using organic analysis and hyperspectral imaging.

In recent years, hyperspectral imaging combined with machine learning techniques has garnered significant attention for its potential in assessing fruit maturity. This study proposes a method for predicting strawberry fruit maturity based on the harvest time. The main features of this study are as follows. 1) Selection of wavelength band associated with strawberry growth season; 2) Extraction of efficient parameters to predict strawberry maturity 3) Prediction of internal quality attributes of strawberries using extracted parameters. In this study, experts cultivated strawberries in a controlled environment and performed hyperspectral measurements and organic analyses on the fruit with minimal time delay to facilitate accurate modeling. Data augmentation techniques through cross-validation and interpolation were effective in improving model performance. The four parameters included in the model and the cumulative value of the model were available for quality prediction as additional parameters. Among these five parameter candidates, two parameters with linearity were finally identified. The predictive outcomes for firmness, soluble solids content, acidity, and anthocyanin levels in strawberry fruit, based on the two identified parameters, are as follows: The first parameter, ps, demonstrated RMSE performances of 1.0 N, 2.3 %, 0.1 %, and 2.0 mg per 100 g fresh fruit for firmness, soluble solids content, acidity, and anthocyanin, respectively. The second parameter, p3, showed RMSE performances of 0.6 N, 1.2 %, 0.1 %, and 1.8 mg per 100 g fresh fruit, respectively. The proposed non-destructive analysis method shows the potential to overcome the challenges associated with destructive testing methods for assessing certain internal qualities of strawberry fruit.

Relationship between continuous EEG monitoring findings and prognostic factors in patients with status epilepticus.

BACKGROUND AND PURPOSE: Little information is available regarding the use of continuous electroencephalography (cEEG) monitoring findings to predict the prognosis of patients with status epilepticus, which could aid in prognostication. This study investigated the relationship between cEEG monitoring findings and various prognostic indicators in patients with status epilepticus. METHODS: We reviewed the clinical profiles and cEEG monitoring data of 28 patients with status epilepticus over a ten-year period. Patient demographics, etiology, EEG features, duration of hospital stay, number of antiseizure medications, and outcome measures were analyzed. Functional outcomes were assessed using the modified Rankin Scale (mRS), which evaluates the degree of daily living impairment and dependence on others resulting from neurological injury. RESULTS: Patients exhibiting electrographic status epilepticus (ESE) demonstrated significantly longer duration of status epilepticus (77.75 ± 58.25 vs. 39.86 ± 29.81 h, p = 0.024) and total length of hospital stay (13.00 ± 6.14 vs. 8.14 ± 5.66 days, p = 0.038) when compared to those with ictal-interictal continuum (IIC). Individuals who displayed any increase in modified Rankin Scale (mRS) score between their premorbid state and discharge also had significantly longer duration of status epilepticus (74.09 ± 34.94 vs. 51.56 ± 54.25 h, p = 0.041) and total length of hospital stay (15.89 ± 6.05 vs. 8.05 ± 4.80 days, p = 0.004) when compared to those who showed no difference. The most prevalent etiology of status epilepticus in our study was chronic structural brain lesions. CONCLUSIONS: This suggests that ESE may serve as a predictor of prolonged duration of status epilepticus and increased hospitalization among patients with status epilepticus.

A novel strategy and characteristics of PVA/citric acid cross-linked hydrophilic elastic sponge of cellulose based on medicinal herb residue.

A new ultra-hydrophilic elastic sponge composite has been proposed. Medicinal herbs, commonly used in herbal medicine and subsequently discarded, are rich in natural polymer substances, making them promising candidates for various material industries. TEMPO-oxidized cellulose was extracted from medicinal herb residue, and the physicochemical properties of an ultra-hydrophilic elastic sponge, prepared through a PVA and CA impregnate cross-linking process, were investigated. The fabricated composite sponge exhibited an increase in compressive stress-strain proportional to the PVA cross-linking concentration, and its water retention capability was assessed through retention tests. Swelling tests for various solvents were conducted to evaluate the potential use of the sponge in diverse industries, revealing the highest swelling ratio in water. Pressure distribution measurements using prescale film indicated that the sponge's shock absorption capacity was enhanced by PVA cross-linking, leading to improved pressure dispersion.

Natural peloids originating from subsea depths of 200 m in the hupo basin, South Korea: physicochemical properties for potential pelotherapy applications.

The present study firstly reports surface sediment from the subsea depth of 200 m as a potential natural peloid. The fine-silt sediment exhibited a consistent clay mineral composition dominated by illite, chlorite, kaolinite, and diatomite. The most abundant clay mineral was illite/mica, with other minerals loosely packed in a face-to-face orientation. The thermal conductivity, specific heat capacity, and cation-exchange capacity of the sediment were in the range 0.855-0.885 W/m K, 2.718-2.821 J/g °C, and 23.06-32.96 cmol/kg, respectively. The concentrations of most toxic elements in the sediment were considerably lower than the limits set by domestic cosmetic regulations and other international standards. The analyzed samples exhibited similar properties to those of previously reported peloids, thus making them suitable for use in the field of pelotherapy; furthermore, the consistency in data across a wide peloid-distribution area is expected to enable economically viable mining. Future investigations should aim to to evaluate the long-term effects on the skin, the bioavailability of potentially hazardous substances, and the therapeutic efficacy for various skin conditions.

Shifts in Clinical Characteristics, Treatment, and Outcome for Rheumatic Mitral Stenosis: Insights From a 20-Year Multicentre Registry Study in Korea.

BACKGROUND: The rapid economic development of South Korea provides a unique model to study changes in the clinical characteristics, treatment approaches, and clinical outcomes of patients with rheumatic mitral stenosis (MS) relative to socioeconomic growth. METHODS: From the Multicenter mitrAl STEnosis with Rheumatic etiology (MASTER) registry, 2,337 patients diagnosed with moderate or severe rheumatic MS between January 2001 and December 2020 were analyzed. Patients were grouped into consecutive 5-year intervals based on their year of diagnosis. Clinical characteristics, echocardiographic data, and clinical outcomes were assessed. RESULTS: Over 20 years, the severity of mitral stenosis increased from 79.1% to 90.2%; similarly, the average age at diagnosis increased from 54.3 to 63.0 years (all P < 0.001). Comorbidities such as hypertension and atrial fibrillation increased (6.3% to 29.5% and 41.4% to 46.9%, respectively; all P for trend < 0.05). The rate of mitral intervention within five years after diagnosis increased from 31.2% to 47.4% (P for trend < 0.001). However, clinical outcomes of rheumatic mitral stenosis deteriorated over time in the composite outcomes (log-rank test, P < 0.001). Conversely, the incidence of stroke remained stable (60.6-73.7%; P < 0.001), which might be attributed to the increased use of anticoagulation therapy. CONCLUSION: This study observed an increase in patient age, comorbidities, and valve disease severity as the country transitioned from a developing to developed status. Despite a rise in mitral valve interventions, clinical outcomes deteriorated over 20 years, highlighting the need for modified treatment approaches to improve patient outcomes.

Validation of TRI-SCORE for Outcome Prediction After Isolated Tricuspid Valve Surgery in Asian Patients.

BACKGROUND: TRI-SCORE was recently developed in Europe as a risk model for predicting in-hospital death after isolated tricuspid valve surgery. We aimed to validate TRI-SCORE in an Asian population and investigate its value for predicting long-term outcomes. METHODS AND RESULTS: The TRI-SCORE was calculated for 202 patients (65±11 years, 61% women, 81% functional tricuspid regurgitation) who underwent isolated tricuspid valve surgery for severe tricuspid regurgitation at 2 Korean centers and was based on 8 parameters: age, New York Heart Association class, right-sided heart failure signs, furosemide daily dose, glomerular filtration rate, bilirubin, left ventricular ejection fraction, and moderate/severe right ventricular dysfunction. The primary outcome was all-cause death during follow-up; the secondary outcome was in-hospital death. During a median follow-up duration of 50 (interquartile range, 21-82) months after isolated tricuspid valve surgery, 23 (11.4%) patients experienced the primary outcome, and 7 (3.5%) patients experienced the secondary outcome. Observed all-cause death and in-hospital death increased by up to 50% in those with higher scores. Patients with the primary outcome had a higher TRI-SCORE (4.5±2.4 versus 2.9±2.1; P=0.001) than those without. The TRI-SCORE showed a significant association with the primary outcome (concordance index, 0.77, cutoff value, 4) and in-hospital death (area under the curve, 0.84; cutoff value, 3). Using the Kaplan-Meier analysis, patients with a high TRI-SCORE exhibited a poor outcome for all-cause death at follow-up (log-rank P<0.001) and in-hospital death (log-rank P=0.004). CONCLUSIONS: TRI-SCORE was validated in an Asian population and helped predict long-term outcomes after isolated tricuspid valve surgery.

Optimizing Percutaneous Mitral Valvuloplasty for Rheumatic Mitral Stenosis　- Clinical Significance of Changes in Mitral Valve Area.

BACKGROUND: Percutaneous mitral valvuloplasty (PMV) is a standard treatment for severe rheumatic mitral stenosis (RMS). However, the prognostic significance of the change in mitral valve area (∆MVA) during PMV is not fully understood.Methods and Results: This study analyzed data from the Multicenter mitrAl STEnosis with Rheumatic etiology (MASTER) registry, which included 3,140 patients with severe RMS. We focused on patients with severe RMS undergoing their first PMV. Changes in echocardiographic parameters, including MVA quantified before and after PMV, and composite outcomes, including mitral valve reintervention, heart failure admission, stroke, and all-cause death, were evaluated. An optimal result was defined as a postprocedural MVA ≥1.5 cm2without mitral regurgitation greater than Grade II. Of the 308 patients included in the study, those with optimal results and ∆MVA >0.5 cm² had a better prognosis (log-rank P<0.001). Patients who achieved optimal results but with ∆MVA ≤0.5 cm² had a greater risk of composite outcomes than those with optimal outcomes and ∆MVA >0.5 cm² (nested Cox regression analysis, hazard ratio 2.27; 95% confidence interval 1.09-4.73; P=0.028). CONCLUSIONS: Achieving an increase in ∆MVA of >0.5 cm2was found to be correlated with improved outcomes. This suggests that, in addition to achieving traditional optimal results, targeting an increase in ∆MVA of >0.5 cm2could be a beneficial objective in PMV treatment for RMS.

Extracellular synthesis of silver nanoparticle using yeast extracts: antibacterial and seed priming applicationss.

The evolution and rapid spread of multidrug-resistant (MDR) bacterial pathogens have become a major concern for human health and demand the development of alternative antimicrobial agents to combat this emergent threat. Conventional intracellular methods for producing metal nanoparticles (NPs) using whole-cell microorganisms have limitations, including binding of NPs to cellular components, potential product loss, and environmental contamination. In contrast, this study introduces a green, extracellular, and sustainable methodology for the bio-materialization of silver NPs (AgNPs) using renewable resource cell-free yeast extract. These extracts serve as a sustainable, biogenic route for both reducing the metal precursor and stabilizing the surface of AgNPs. This method offers several advantages such as cost-effectiveness, environment-friendliness, ease of synthesis, and scalability. HR-TEM imaging of the biosynthesized AgNPs revealed an isotropic growth route, resulting in an average size of about ~ 18 nm and shapes ranging from spherical to oval. Further characterization by FTIR and XPS results revealed various functional groups, including carboxyl, hydroxyl, and amide contribute to enhanced colloidal stability. AgNPs exhibited potent antibacterial activity against tested MDR strains, showing particularly high efficacy against Gram-negative bacteria. These findings suggest their potential role in developing alternative treatments to address the growing threat of antimicrobial resistance. Additionally, seed priming experiments demonstrated that pre-sowing treatment with AgNPs improves both the germination rate and survival of Sorghum jowar and Zea mays seedlings. KEY POINTS: •Yeast extract enables efficient, cost-effective, and eco-friendly AgNP synthesis. •Biosynthesized AgNPs showed strong antibacterial activity against MDR bacteria. •AgNPs boost seed germination and protect against seed-borne diseases.

Outcomes of Severe Mitral Stenosis With the Revised Severity Criteria: Mitral Valve Replacement vs Percutaneous Mitral Valvuloplasty.

BACKGROUND: This study aimed to compare the outcomes, according to percutaneous mitral valvuloplasty (PMV) vs mitral valve replacement (MVR), of severe mitral stenosis (MS) with the updated criteria (MVA ≤ 1.5 cm2). METHODS: From the Multicenter Mitral Stenosis With Rheumatic Etiology (MASTER) registry of 3140 patients, we included patients with severe MS who underwent PMV or MVR between January 2000 and December 2021 except for previous valvular surgery/intervention, at least moderate other valvular dysfunction, and thrombus at the left atrium/appendage. Moderately severe MS (MS-MS) and very severe MS (VS-MS) were defined as 1.0 cm2 < MVA ≤ 1.5 cm2 and MVA ≤ 1.0 cm2, respectively. Primary outcomes were a composite of cardiovascular (CV) death and heart failure (HF) hospitalization. Secondary outcomes were a composite of primary outcomes and redo intervention. RESULTS: Among 442 patients (mean 56.5 ±11.9 years, women 77.1%), the MVR group (n = 260) was older, had more comorbidities, higher echoscore, larger left chambers, and higher right ventricular systolic pressure than the PMV group (n = 182). During a mean follow-up of 6.9 ± 5.2 years with inverse probability-weighted matching, primary outcomes did not differ, but the MVR group experienced fewer secondary outcomes (P = 0.010). In subgroup analysis of patients with MS-MS and VS-MS, primary outcomes did not differ. However, the MVR group in patients with VS-MS showed better secondary outcomes (P = 0.012). CONCLUSIONS: PMV or MVR did not influence CV mortality or HF hospitalization in both MS-MS and VS-MS. However, because of increased early redo intervention in the PMV group in VS-MS, MVR would be the preferable option without clear evidence of suitable morphology for PMV.

Alginic acid-functionalized silver nanoparticles: A rapid monitoring tool for detecting the technology-critical element tellurium.

The increasing global demand for tellurium, driven by its critical role in alloys, photovoltaic devices, and electronics, has raised concerns about its environmental pollution and neurotoxicity. In response, the potential of alginic acid (AA), a renewable, low-cost, and sustainable biopolymer, was explored for the biosynthesis of ultra-small silver nanoparticles (AgNPs) and their application in the detection of tellurium (Te(IV)). The effect of key synthesis parameters on desired physicochemical properties and yield of AgNPs was established to ensure high specificity and sensitivity towards Te(IV). The purified AgNPs with AA surface ligands were utilized to demonstrate a ratiometric absorbance sensor that exhibits excellent linearity and nanomolar-level affinity. This approach achieved a high correlation coefficient of ∼ 0.982, with a low detection limit of about 22 nM. Further investigations into the effect of pH, ionic strength, and organic molecules were conducted to elucidate detection performance and molecular understanding. The detection mechanism relies on the coordination between Te(IV) ions and the carboxylate groups of AA, which initiates aggregation-induced plasmon coupling in adjacent AgNPs. The capability of this analytical method to monitor Te(IV) in real-world water samples features its rapidity, user-friendliness, and suitability for point-of-care monitoring, making it a promising alternative to more complex techniques.

Real-time Neural Connectivity Inference with Presynaptic Spike-driven Spike Timing-Dependent Plasticity.

Brain-like artificial intelligence in electronics can be built efficiently by understanding the connectivity of neuronal circuitry. The concept of neural connectivity inference with a two-dimensional cross-bar structure memristor array is indicated in recent studies; however, large-scale implementation is challenging owing to device variations and the requirement of online parameter adaptation. This study proposes a neural connectivity inference method with one-dimensional spiking neurons using spike timing-dependent plasticity and presynaptic spike-driven spike timing-dependent plasticity learning rules, designed for a large-scale neuromorphic system. The proposed learning process decreases the number of spiking neurons by half. We simulate 12 ground-truth neural networks comprising one-dimensional eight and 64 neurons. We analyze the correlation between the neural connectivity of the ground truth and spiking neural networks using the Matthews correlation coefficient. In addition, we analyze the sensitivity and specificity of inference. Validation using the presynaptic spike-driven spike timing-dependent plasticity learning rule implies a potential approach for large-scale neural network inference with real hardware realization of large-scale neuromorphic systems.

Fatigue or excessive daytime sleepiness: which is more closely related to depression?

OBJECTIVE/BACKGROUND: This study investigated fatigue and excessive daytime sleepiness to determine which was more closely related to depression in the general population. PATIENTS/METHODS: Participants were investigated across 15 South Korean districts. Excessive daytime sleepiness, fatigue, and depression were evaluated using the Epworth Sleepiness Scale (ESS), Fatigue Severity Scale (FSS), and Patient Health Questionnaire-9 (PHQ-9), respectively. Depression was defined as PHQ-9 ≥ 10. The authors classified the combination of excessive daytime sleepiness and fatigue as excessive daytime sleepiness with fatigue (E+F+, ESS ≥ 11, FSS ≥ 36), fatigue without excessive daytime sleepiness (E-F+, ESS < 11, FSS ≥ 36), excessive daytime sleepiness without fatigue (E+F-, ESS ≥ 11, FSS < 36), and no fatigue and excessive daytime sleepiness (E-F-, ESS < 11, FSS < 36). RESULTS: Among 2,493 participants (1,257 women), mean age was 47.9 ± 0.3 years. The prevalence of depression, fatigue, and excessive daytime sleepiness was 8.4% (n = 210), 30.8% (n = 767), and 15.3% (n = 382), respectively. The frequency of the four categories with depression (vs. controls) was as follows.: E+F+ (n = 67, 31.9% vs. 7.3%) (P < 0.001), E-F+ (n = 71, 33.8% vs. 20.3%) (P < 0.001), E+F-( n = 16, 7.6% vs. 5.8%) (P = 0.294), and E-F- (n = 56, 26.7% vs. 66.6%) (P < 0.001). After adjusting for covariates, depression was associated with E+F+ (odds ratio, OR 8.804, 95% confidence interval (CI) 5.818-13.132), E-F+ (OR 3.942, 95% CI 2.704-5.747), E+F- (OR 2.812, 95% CI 1.542-5.131), and E-F- (reference). Additionally, we performed logistic regression according to two categories. There was no significant difference in the association of depression between E+F- (reference) and E-F+ (OR 1.399, 95% CI 0.760-2.575). CONCLUSION: Although fatigue and excessive daytime sleepiness were associated with depression regardless of the presence of each other, we could not clarify which was more closely related to depression.

Analysis of Differences in Single-Joint Movement of Dominant and Non-Dominant Hands for Human-like Robotic Control.

Although several previous studies on laterality of upper limb motor control have reported functional differences, this conclusion has not been agreed upon. It may be conjectured that the inconsistent results were caused because upper limb motor control was observed in multi-joint tasks that could generate different inter-joint motor coordination for each arm. Resolving this, we employed a single wrist joint tracking task to reduce the effect of multi-joint dynamics and examined the differences between the dominant and non-dominant hands in terms of motor control. Specifically, we defined two sections to induce feedback (FB) and feedforward (FF) controls: the first section involved a visible target for FB control, and the other section involved an invisible target for FF control. We examined the differences in the position errors of the tracer and the target. Fourteen healthy participants performed the task. As a result, we found that during FB control, the dominant hand performed better than the non-dominant hand, while we did not observe significant differences in FF control. In other words, in a single-joint movement that is not under the influence of the multi-joint coordination, only FB control showed laterality and not FF control. Furthermore, we confirmed that the dominant hand outperformed the non-dominant hand in terms of responding to situations that required a change in control strategy.

Assessing of exercise intensity for a rhythmik exercise program based on cardiopulmonary functions.

This study investigated the determination of exercise intensity for a rhythmik exercise program based on cardiopulmonary functions. Nine female participants in their 20s to 40s performed a rhythmik exercise program for 60 min per session, three sessions weekly, for 8 weeks. All participants underwent a grade exercise test to measure their minute ventilation (VE), oxygen uptake (VO2), maximal volume of minute oxygen consumption (VO2max), heart rate (HR), and oxygen pulse (O2 pulse) at the time of anaerobic threshold (AT) and maximal exercise time (ETmax). To determine the exercise intensity of the rhythmik exercise program, the Polar Heart Monitor was used for quantification, and the Borg Scale was used to measure the rating of perceived exertion (RPE). We did not observe any significant effects on the reaching time of AT, VE, VO2, VO2max, HR, and O2 pulse at either AT or ETmax. However, maximal value of VE (VEmax) was significantly enhanced at ETmax. The exercise intensity of the rhythmik exercise program was found to be low at 62.85% of HRmax with an RPE of 12.22. Our results suggest that the rhythmik exercise program did not directly improve cardiopulmonary functions; however, considering the unstructured nature of the rhythmik exercise program, anticipated positive effects on cardiopulmonary fitness are achievable through changes in the program contents and exercise time according to the goals of the participants.

Cellulose graphitic carbon directed iron oxide interfaced polypyrrole electrode materials for high performance supercapacitors.

The rising demand for green and clean energy urges the enlargement of economical and proficient electrode materials for supercapacitors. Herein, we designed a novel electrode material by porous cellulose graphitic carbon (CC) derived from bio-waste cornhusk via the pyrolysis route, and α-Fe2O3 decorated nanostructure with CC (CCIO) was achieved in situ pyrolysis of corn-husk and Fe(NO3)3·9H2O metal salt followed by a coating of polypyrrole (CCIOP). The CC, CCIO, and CCIOP nanocomposite electrodes were characterized by XRD, Raman, FTIR, FE-SEM/EDX, FE-TEM, XPS, and BET analysis. The CCIOP nanocomposite electrode exhibits an enhanced specific capacitance (Csp) of 290.9 F/g, which is substantial to its pristine CC (128.3 F/g), PPy (140.3 F/g), and CCIO (190.7 F/g). The Csp of CCIOP in a three-electrode system, using 1 M Na2SO4 electrolyte exhibits excellent capacity retention of 79.1 % even at a high current density of 10 A/g. The as-fabricated asymmetric supercapacitor (ASC) delivered a remarkable capacity retention of 88.7 % with a coulombic efficiency of 98.8 % even after 3000 cycles. The study shows successful utilization of cellulose from bio-waste cornhusk into a substantial template applicable in future alternative energy storage devices.

Deep Representation Learning with Sample Generation and Augmented Attention Module for Imbalanced ECG Classification.

Developing an efficient heartbeat monitoring system has become a focal point in numerous healthcare applications. Specifically, in the last few years, heartbeat classification for arrhythmia detection has gained considerable interest from researchers. This paper presents a novel deep representation learning method for the efficient detection of arrhythmic beats. To mitigate the issues associated with the imbalanced data distribution, a novel re-sampling strategy is introduced. Unlike the existing oversampling methods, the proposed technique transforms majority-class samples into minority-class samples with a novel translation loss function. This approach assists the model in learning a more generalized representation of crucially important minority class samples. Moreover, by exploiting an auxiliary feature, an augmented attention module is designed that focuses on the most relevant and target-specific information. We adopted an inter-patient classification paradigm to evaluate the proposed method. The experimental results of this study on the MIT-BIH arrhythmia database clearly indicate that the proposed model with augmented attention mechanism and over-sampling strategy significantly learns a balanced deep representation and improves the classification performance of vital heartbeats.

Quantitative electroencephalography as a potential biomarker in migraine.

OBJECTIVE: The aim of this study was to investigate the utility of quantitative electroencephalography (QEEG) as a diagnostic tool for migraine and as an indicator of treatment response by comparing QEEG characteristics between migraine patients and controls, and monitoring changes in these characteristics alongside clinical symptoms in response to treatment BACKGROUND: We hypothesized that patients with migraine exhibit distinctive characteristics in QEEG measurements, which could be used as potential diagnostic biomarkers and as a tool for monitoring treatment response. METHODS: A total of 720 patients were included in the study, comprising 619 patients with migraine and 101 subjects as a control group. QEEG measurements were analyzed for absolute power across specific frequency bands: delta wave (0.5-4 Hz), theta wave (4-8 Hz), alpha wave (8-12 Hz), beta wave (12-25 Hz), and high beta wave (25-30 Hz). The absolute power was normalized against a normative dataset from NeuroGuide, with electrodes being highlighted for significance if they exceeded 1.96. Clinical symptoms were also monitored for correlation with QEEG changes. RESULTS: Our analysis showed that patients with migraine exhibited significantly higher absolute power across all frequencies, most markedly within the high beta frequency range. When considering electrodes with z-scores exceeding the threshold of 1.96 in the high beta range, a significant association with migraine diagnosis was observed (per 1 electrode increase, OR 1.06; 95% CI 1.01-1.11; p = .012). Moreover, pre- and posttreatment changes in QEEG measurements corresponded with changes in clinical symptoms. CONCLUSION: Patients with migraine have distinctive QEEG measurements, particularly regarding absolute power and the number of electrodes that surpassed the z-score threshold in high beta wave activity. These findings suggest the potential of QEEG as a diagnostic biomarker and as a tool for monitoring treatment response in migraine patients, warranting further large-scale studies for confirmation and expansion.

Development of Novel Peptide-Modified Silver Nanoparticle-Based Rapid Biosensors for Detecting Aminoglycoside Antibiotics.

The detection and monitoring of aminoglycoside antibiotics (AGAs) have become of utmost importance due to their widespread use in human and animal therapy, as well as the associated risks of exposure, toxicity, and the emergence of antimicrobial resistance. In this study, we successfully synthesized casein hydrolysate peptides-functionalized silver nanoparticles (CHPs@AgNPs) and employed them as a novel colorimetric analytical platform to demonstrate remarkable specificity and sensitivity toward AGAs. The colorimetric and spectral response of the CHPs@AgNPs was observed at 405 and 520 nm, showing a linear correlation with the concentration of streptomycin, a representative AGA. The color changes from yellow to orange provided a visual indication of the analyte concentration, enabling quantitative determination for real-world samples. The AgNP assay exhibited excellent sensitivity with dynamic ranges of approximately 200-650 and 100-700 nM for streptomycin-spiked tap water and dairy whey with limits of detection found to be ∼98 and 56 nM, respectively. The mechanism behind the selective aggregation of CHPs@AgNPs in the presence of AGAs involves the amine groups of the target analytes acting as molecular bridges for electrostatic coupling with hydroxyl or carboxyl functionalities of adjacent NPs, driving the formation of stable NP aggregates. The developed assay offers several advantages, making it suitable for various practical applications. It is characterized by its simplicity, rapidity, specificity, sensitivity, and cost-effectiveness. These unique features make the method a promising tool for monitoring water quality, ensuring food safety, and dealing with emergent issues of antibiotic resistance.

Longitudinal Trends in Sleep and Related Factors Among South Korean Adults From 2009 to 2018.

BACKGROUND AND PURPOSE: Excess or insufficient sleep, irregular sleep-wake patterns, and an extreme early or late chronotypes adversely impact physical and mental health. Changes in sleep characteristics should therefore be tracked, and factors that contribute to poor sleep should be identified. We investigated the changes in sleep patterns among South Korean adults during 2009-2018. METHODS: Using data of a representative sample of South Korean adults from the 2009 (n=2,658, 48.5% males; age=44.5±15.0 years old [mean±standard deviation], age range=19-86 years) and 2018 (n=2,389, 49.1% males; age=47.9±16.3 years, age range=19-92 years) Korean Headache-Sleep Study, we explored changes in sleep timing, sleep duration, chronotype, and social jetlag (SJL). Logistic regression analysis was used to examine the association between average sleep duration and depression. RESULTS: From 2009 to 2018, bedtimes were advanced by 10 and 25 min on workdays and free days, respectively. Meanwhile, wake-up times were advanced by 13 min and delayed by 12 min on workdays and free days, respectively. The average sleep duration significantly decreased from 7.45 h to 7.13 h. The prevalence of short sleep duration (<7 h) increased, whereas that of long sleep duration (≥8 h) decreased. A circadian preference toward eveningness and SJL increased. The prevalence of depression increased from 4.6% to 8.4%, and there were significant reverse J-shaped and U-shaped associations between average sleep duration and depression in 2009 and 2018, respectively. CONCLUSIONS: Changes in sleep patterns and the association between sleep duration and depressive mood were determined from a representative sample of the South Korean adult population. Interventions to modify sleep behaviors might improve public health.