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This study presents an extended gate aptamer-based FET sensor for the detection of mercury ions in water. Heavy metal contamination in water can pose a severe threat to human health, and mercury ions are particularly dangerous as they can accumulate in the human body and cause serious health problems. The sensor provides high selectivity and sensitivity, even in the presence of other heavy metals, and achieves a detection limit of 0.2 ppm using a 500 μm x 500 μm gate sensing area. This cost-effective and efficient method can contribute to the mitigation of environmental pollution and the protection of public health.

Normal ECG standards in newborns, infants, children and adolescents have been collected and published by many authors. Only those by Davignon et al., Rijinbeek et al. and our two studies covered all ages from birth to adolescence. The standards reflecting the growth and development of the heart in infants, children and adolescents remained to be studied and explored.We selected from our ECG database, after discussions and consultation, 15 key ECG parameters and analyzed for their age- and sex-specific mean, standard deviation and 2nd to 98th percentiles and their percentile charts were constructed.The ranges and distributions of the normal ECG standards, means and 2nd to 98th percentiles of 15 key parameters were established.A complete set of normal ECG standards of 15 key parameters from birth to adolescents is available for clinicians and researchers.

The reduction of the agricultural workforce due to the rapid development of technology has resulted in labor shortages. Agricultural mechanization, such as drone use for pesticide spraying, can solve this problem. However, the terrain, culture, and operational limitations in mountainous orchards in Taiwan make pesticide spraying challenging. By combining reinforcement learning with deep neural networks, we propose to train drones to avoid obstacles and find optimal paths for pesticide spraying that reduce operational difficulties, pesticide costs, and battery consumption. We experimented with different reward mechanisms, neural network depths, flight direction granularities, and environments to devise a plan suitable for sloping orchards. Reinforcement learning is more effective than traditional algorithms for solving path planning in complex environments. &nbsp

Achieving robust cross contexts speech emotion recognition (SER) has become a critical next direction of research for wide adoption of SER technology. The core challenge is in the large variability of affective speech that is highly contextualized. Prior works have worked on this as a transfer learning problem that mostly focuses on developing domain adaptation strategy. However, many of the existing speech emotion corpora, even those considered as large scale, are still limited in size resulting in an unsatisfactory transfer result. On the other hand, directly collecting context-specific corpus often results in an even smaller data size leading to an inevitably non-robust accuracy. In order to mitigate this issue, we propose the concept of enhancing the affect-related variability when learning the in-context acoustic latent representation by integrating out-of-context emotion data. Specifically, we utilize adversarial autoencoder network as our backbone with multiple out-of-context emotion labels derived for each in-context samples that serve as an auxiliary constraint in learning the latent representation. We extensively evaluate our framework using three in-context databases with three out-of-context databases. In this work, we demonstrate not only an improved recognition accuracy but also a comprehensive analysis on the effectiveness of this representation learning strategy.

BACKGROUND/PURPOSE: :Both periodontal disease and diabetes mellitus (DM) are long-term inflammatory disorders that are highly prevalent and have a significant health impact. Inflammaging, a state of pre-aging and hyperinflammatory state has been acknowledged for its role in DM patients to have heightened risk of periodontitis. Numerous evidences revealed that inflammaging contributed by cell senescence, acceleration of inflammation and oxidative stress participates in the destruction of periodontium in DM. Abilities of vitamin D in suppressing inflammation and oxidative stress have been revealed in a range of tissues, however in DM’s gingival cells, the effect remain undefined. MATERIALS AND METHODS: : Under the stimulation of advanced glycation end-products (AGEs), we assessed the cell proliferation in human gingival fibroblast (HGF), IL-6 and IL-8 secretions, cellular senescence expression and generation of reactive oxygen species (ROS) with or without vitamin D intervention. Following that, we examined the expression of Nrf2 and HO-1 to see if vitamin D was able to modulate the anti-oxidant signaling. A knockdown experiment was then conducted to proof the participation of Nrf2 on the secretion of pro-inflammatory IL-6 and IL-8. RESULTS: : Following the treatment of vitamin D, AGEs-elicited IL-6 and IL-8 production and cell senescence were dose-dependently repressed. Moreover, vitamin D attenuated AGEs-induced ROS in a dose-dependent pattern. Results from qRT-PCR demonstrated vitamin D reversed the suppression of Nrf2 and HO-1 induced by AGEs. Our findings revealed that the anti-inflammatory and anti-oxidant effect in vitamin D was mediated via the upregulation of Nrf2 expression. CONCLUSION: : These data showed that high levels of AGEs in the gingiva lead to inflammaging reflected by increased pro-inflammatory cytokines, cell senescence expression and oxidative stress. Vitamin D supplementation can reduce oxidative stress and inflammation via the upregulation of Nrf2 signaling and hence, may be a potential approach for treatment of diabetes-associated periodontitis.

New tetracycline derivatives exhibit broad-spectrum antimicrobial activities. This study aimed to assess the in vitro activity of eravacycline against common Enterobacterales.Clinical Enterobacterales isolates were collected between 2017 and 2021. The minimum inhibitory concentration (MIC) was determined using a broth microdilution test.We identified Klebsiella pneumoniae (n = 300), Escherichia coli (n = 300), Klebsiella oxytoca (n = 100), Enterobacter cloacae complex (n = 100), Citrobacter freundii (n = 100), and Proteus mirabilis (n = 100). All P. mirabilis strains were resistant to eravacycline. Excluding P. mirabilis, the susceptibility rates to eravacycline, omadacycline, and tigecycline were 75.2%, 66.9%, and 73%, respectively. The MICThis study provides the MIC and susceptibility rate of eravacycline for common Enterobacterales. Eravacycline could be a therapeutic choice for cefotaxime non-susceptible or meropenem non-susceptible Enterobacterales, especially K. oxytoca, C. freundii, and E. coli.

Background: High-fidelity meteorological data is a prerequisite for the realistic simulation of atmospheric dispersion of radioactive materials near nuclear power plants (NPPs). However, many meteorological models frequently overestimate near-surface wind speeds, failing to represent local meteorological conditions near NPPs. This study presents a new high-resolution (approximately 1 km) meteorological downscaling method for modeling short-range (< 100 km) atmospheric dispersion of accidental NPP plumes.Materials and Methods: Six considerations from literature reviews have been suggested for a new dynamic downscaling method. The dynamic downscaling method is developed based on the Weather Research and Forecasting (WRF) model version 3.6.1, applying high-resolution land-use and topography data. In addition, a new subgrid-scale topographic drag parameterization has been implemented for a realistic representation of the atmospheric surface-layer momentum transfer. Finally, a year-long simulation for the Kori and Wolsong NPPs, located in southeastern coastal areas, has been made for 2016 and evaluated against operational surface meteorological measurements and the NPPs’ on-site weather stations.Results and Discussion: The new dynamic downscaling method can represent multiscale atmospheric motions from the synoptic to the boundary-layer scales and produce three-dimensional local meteorological fields near the NPPs with a 1.2 km grid resolution. Comparing the year-long simulation against the measurements showed a salient improvement in simulating near-surface wind fields by reducing the root mean square error of approximately 1 m/s. Furthermore, the improved wind field simulation led to a better agreement in the Eulerian estimate of the local atmospheric dispersion. The new subgrid-scale topographic drag parameterization was essential for improved performance, suggesting the importance of the subgrid-scale momentum interactions in the atmospheric surface layer.Conclusion: A new dynamic downscaling method has been developed to produce high-resolution local meteorological fields around the Kori and Wolsong NPPs, which can be used in short-range atmospheric dispersion modeling near the NPPs.

Background and ObjectivesDiabetes mellitus (DM) contributes significantly to metabolic syndrome and cardiovascular events, and it may be a comorbidity of epilepsy. The objective of this study was to investigate whether long-term antiseizure medication (ASM) use is associated with the risk of developing type 2 diabetes.MethodsWe analyzed data from the Chang Gung Research Database. Patients aged ≥45 years who received ASM treatment from January 2001 to May 2019 were identified. Patients with DM-associated diseases and short-term ASM use were excluded. The patients were classified into nonenzyme interaction, enzyme-inducing, enzyme-inhibiting, and mixed ASM groups. The rate of incident diabetes associated with individual ASM was further analyzed. Propensity score weighting was performed to balance between-group differences. Analyses were conducted with Cox proportional regression models and stabilized inverse probability of treatment weighting (IPTW). Hazard ratios (HRs) were calculated at 3, 4, 6, and 9 years after the index date and the end of follow-up.ResultsA total of 5,103 patients were analyzed, of whom 474 took nonenzyme interaction ASMs, 1,156 took enzyme-inducing ASMs, 336 took enzyme-inhibiting ASMs, and 3,137 took mixed ASMs. During follow-up (39,248 person-years), 663 patients developed new-onset DM, and the prevalence was 13.0%. The incidence of DM plateaued at 6–9 years after ASM initiation. Enzyme-inhibiting ASMs were significantly associated with a higher HR starting at the third year and then throughout the study period. The HRs were 1.93 (95% CI 1.33–2.80), 1.85 (95% CI 1.24–2.75), and 2.08 (95% CI 1.43–3.03) in unadjusted, adjusted, and stabilized IPTW models, respectively, at the end of follow-up. The dosing of ASM did not increase the risk of DM, and none of the individual ASM analyses reached statistical significance.DiscussionThe long-term use of enzyme-inhibiting ASMs was associated with an increased risk of incident DM, and the risk increased with the duration of treatment. These findings may guide the choice of drugs in those requiring long-term ASM therapy, particularly in high-risk individuals.Classification of EvidenceThis study provides Class IV evidence that enzyme-inhibiting ASMs were associated with an increased risk of developing DM compared with nonenzyme interaction ASMs.

Background: Currently, the standard of treatment for trimalleolar (TM) fracture is osteosynthesis through open reduction and internal fixation (ORIF). This study assessed whether arthroscopically assisted reduction and minimally invasive surgery (AARMIS) can be an alternative surgical method for TM fractures. Methods: This retrospective cohort study included 49 patients with TM that were surgically treated. 27 patients received ORIF and 22 patients underwent AARMIS . At baseline, we recorded the patient’s demographic features, fracture pattern (AO-OTA and Haraguchi classification), and surgical method. For postoperative results, we examined the patient’s radiographic outcome, including time to union, quality of fracture reduction, as well as functional outcomes (American Orthopaedic Foot & Ankle Society ankle hindfoot score, ankle range of motion, and visual analog scale of pain) and perioperative complications. Results: At mean follow-up of 46.6[Formula: see text] (ORIF) and 36.4[Formula: see text] months (AARMIS), both groups had comparable radiographic outcomes. No significant difference in rates of early ankle OA were detected. In terms of functional outcome, VAS pain and AOFAS score at postoperative day 3, postoperative month 3, and at final follow-up were not different. In terms of range of motion, we did not find a significant difference in mean range of motion. Conclusion: Patients with TM fractures treated with AARMIS achieved satisfactory results and was not significantly different in radiographic and functional performance compared with ORIF. Level of Evidence: Level III, retrospective cohort study.