The objective of this study is to develop a convolutional neural network (CNN) for computed tomography (CT) image super-resolution. The network learns an end-to-end mapping between low (thick-slice ...thickness) and high (thin-slice thickness) resolution images using the modified U-Net. To verify the proposed method, we train and test the CNN using axially averaged data of existing thin-slice CT images as input and their middle slice as the label. Fifty-two CT studies are used as the CNN training set, and 13 CT studies are used as the test set. We perform five-fold cross-validation to confirm the performance consistency. Because all input and output images are used in two-dimensional slice format, the total number of slices for training the CNN is 7670. We assess the performance of the proposed method with respect to the resolution and contrast, as well as the noise properties. The CNN generates output images that are virtually equivalent to the ground truth. The most remarkable image-recovery improvement by the CNN is deblurring of boundaries of bone structures and air cavities. The CNN output yields an approximately 10% higher peak signal-to-noise ratio and lower normalized root mean square error than the input (thicker slices). The CNN output noise level is lower than the ground truth and equivalent to the iterative image reconstruction result. The proposed deep learning method is useful for both super-resolution and de-noising.
OBJECTIVETo elucidate longitudinal changes in the dopamine transporter (DAT) availability in association with the prodromal markers in idiopathic REM sleep behavior disorder (iRBD), we analyzed a ...longitudinal prospective iRBD cohort data.
METHODThe study cohort consisted of patients with iRBD, individuals with Parkinson disease (PD), and healthy controls. All participants were evaluated for olfaction, neuropsychological tests, and the Movement Disorders Society–Unified Parkinsonʼs Disease Rating Scale and underwent F-FP-CIT PET scans every 2 years. We calculated the DAT pattern by performing the principal component analysis of tracer uptakes in 6 striatal regions.
RESULTDAT patterns in patients with iRBD with baseline hyposmia, constipation, and mild parkinsonian signs distributed toward the PD pattern and clearly distinguished from the healthy control pattern. The DAT pattern moved toward the PD pattern over time in some patients with iRBD during the follow-up, and baseline hyposmia was the only biomarker significantly associated with this change. Baseline PD pattern of DAT predicted 58% of disease converters (hazard ratio 4.95 95% confidence interval 1.16–21.08). The combination of hyposmia and baseline PD pattern of DAT predicted 67% of the conversion (hazard ratio 7.89 confidence interval 1.85–33.69). The estimated sample size required for a simulated neuroprotective clinical trial was 63 per group when the annual change of DAT pattern was used as an outcome in the subgroup with baseline DAT PD pattern and hyposmia, which is the smallest number reported so far.
CONCLUSIONBaseline and longitudinal monitoring of the DAT pattern can be a useful biomarker in identifying individuals with a high risk of disease conversion and in selecting the potential population for clinical trials in iRBD.
Nanomaterials are used in diverse fields including food, cosmetic, and medical industries. Titanium dioxide nanoparticles (TiO2-NP) are widely used, but their effects on biological systems and ...mechanism of toxicity have not been elucidated fully. Here, we report the toxicological mechanism of TiO2-NP in cell organelles. Human bronchial epithelial cells (16HBE14o-) were exposed to 50 and 100 μg/mL TiO2-NP for 24 and 48 h. Our results showed that TiO2-NP induced endoplasmic reticulum (ER) stress in the cells and disrupted the mitochondria-associated endoplasmic reticulum membranes (MAMs) and calcium ion balance, thereby increasing autophagy. In contrast, an inhibitor of ER stress, tauroursodeoxycholic acid (TUDCA), mitigated the cellular toxic response, suggesting that TiO2-NP promoted toxicity via ER stress. This novel mechanism of TiO2-NP toxicity in human bronchial epithelial cells suggests that further exhaustive research on the harmful effects of these nanoparticles in relevant organisms is needed for their safe application.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Herein, high-performance, reliable electrochromic supercapacitors (ECSs) are proposed based on tungsten trioxide (WO3) and nickel oxide (NiO) films. To maximize device performance and stability, the ...stoichiometric balance between anode and cathode materials is controlled by carefully adjusting the thickness of the anodic NiO film while fixing the thickness of WO3 to ∼660 nm. Then, a small amount (≤10 mol %) of metal (e.g., copper) is doped into the NiO film, improving the electrical conductivity and electrochemical activity. At a Cu doping level of 7 mol %, the resulting ECS exhibited the highest performance, including a high areal capacitance (∼14.9 mF/cm2), excellent coulombic efficiency (∼99%), wide operating temperature range (0–80 °C), reliable operation with high charging/discharging cyclic stability (>10,000 cycles), and good self-discharging durability. Simultaneously, the change in transmittance of the device is well synchronized with the galvanostatic charging/discharging curve by which the real-time energy storage status is visually indicated. Furthermore, the practical feasibility of the device is successfully demonstrated. These results imply that the ECS fabricated in this work is a promising potential energy storage platform and an attractive component for future electronics.
Abstract The antimicrobial effects of silver (Ag) ion or salts are well known, but the effects of Ag nanoparticles on microorganisms and antimicrobial mechanism have not been revealed clearly. Stable ...Ag nanoparticles were prepared and their shape and size distribution characterized by particle characterizer and transmission electron microscopic study. The antimicrobial activity of Ag nanoparticles was investigated against yeast, Escherichia coli , and Staphylococcus aureus . In these tests, Muller Hinton agar plates were used and Ag nanoparticles of various concentrations were supplemented in liquid systems. As results, yeast and E. coli were inhibited at the low concentration of Ag nanoparticles, whereas the growth-inhibitory effects on S. aureus were mild. The free-radical generation effect of Ag nanoparticles on microbial growth inhibition was investigated by electron spin resonance spectroscopy. These results suggest that Ag nanoparticles can be used as effective growth inhibitors in various microorganisms, making them applicable to diverse medical devices and antimicrobial control systems.
To elucidate the role of Parkinson's disease (PD)-related brain metabolic patterns as a biomarker in isolated rapid-eye-movement sleep behavior disorder (iRBD) for future disease conversion.
This is ...a prospective cohort study consisting of 30 iRBD patients, 25 de novo PD patients with a premorbid history of RBD, 21 long-standing PD patients on stable treatment and 24 healthy controls. iRBD group was longitudinally followed up. All participants underwent
F-Fluorodeoxyglucose (FDG) PET and were evaluated with olfaction, cognition, and the Movement disorders society-Unified PD Rating Scale (MDS-UPDRS) at baseline. From FDG-PET scans, we derived metabolic patterns from the long-standing PD group (PD-RP) and de novo PD group with RBD (dnPDRBD-RP). Subsequently, we calculated the PD-RP and dnPDRBD-RP scores in iRBD patients. We validated the metabolic patterns in each PD group and separate iRBD cohort (
=14).
The two patterns significantly correlated with each other and were spatially overlapping yet distinct. The MDS-UPDRS motor scores significantly correlated with PD-RP (
= 0.013) but not with dnPDRBD-RP (
= 0.076). In contrast, dnPDRBD-RP correlated with olfaction in butanol threshold test (
= 0.018) in iRBD subjects, but PD-RP did not (
= 0.21). High dnPDRBD-RP in iRBD patients predicted future phenoconversion with all cut-off ranges from 1.5 to 3 standard deviations of the control value, whereas predictability of PD-RP was only significant in a partial range of cut-off.
The dnPDRBD-RP is an efficient neuroimaging biomarker that reflects prodromal features of PD and predicts phenoconversion in iRBD that can be applied individually.
This study provides Class IV evidence that a de novo Parkinson's disease pattern on FDG-PET predict future conversion to neurodegenerative disease in patients with isolated rapid-eye-movement sleep behavior disorder (iRBD).
Purpose
Although functional brain imaging has been used for the early and objective assessment of cognitive dysfunction, there is a lack of generalized image-based biomarker which can evaluate ...individual’s cognitive dysfunction in various disorders. To this end, we developed a deep learning-based cognitive signature of FDG brain PET adaptable for Parkinson’s disease (PD) as well as Alzheimer’s disease (AD).
Methods
A deep learning model for discriminating AD from normal controls (NCs) was built by a training set consisting of 636 FDG PET obtained from Alzheimer’s Disease Neuroimaging Initiative database. The model was directly transferred to images of mild cognitive impairment (MCI) patients (
n
= 666) for identifying who would rapidly convert to AD and another independent cohort consisting of 62 PD patients to differentiate PD patients with dementia. The model accuracy was measured by area under curve (AUC) of receiver operating characteristic (ROC) analysis. The relationship between all images was visualized by two-dimensional projection of the deep learning-based features. The model was also designed to predict cognitive score of the subjects and validated in PD patients. Cognitive dysfunction-related regions were visualized by feature maps of the deep CNN model.
Results
AUC of ROC for differentiating AD from NC was 0.94 (95% CI 0.89–0.98). The transfer of the model could differentiate MCI patients who would convert to AD (AUC = 0.82) and PD with dementia (AUC = 0.81). The two-dimensional projection mapping visualized the degree of cognitive dysfunction compared with normal brains regardless of different disease cohorts. Predicted cognitive score, an output of the model, was highly correlated with the mini-mental status exam scores. Individual cognitive dysfunction-related regions included cingulate and high frontoparietal cortices, while they showed individual variability.
Conclusion
The deep learning-based cognitive function evaluation model could be successfully transferred to multiple disease domains. We suggest that this approach might be extended to an objective cognitive signature that provides quantitative biomarker for cognitive dysfunction across various neurodegenerative disorders.
► Potential toxicity and mechanism of ZnO-np were assessed in normal skin cells. ► ZnO-np induces ROS generation in normal skin cells. ► ZnO-np induces autophagy accumulation and leads to cell death. ...► ZnO-np affects to mitochondria disruption and dysfunction.
Zinc oxide nanoparticles (ZnO-np) are used in an increasing number of industrial products such as paint, coating and cosmetics, and in other biological applications. There have been many suggestions of a ZnO-np toxicity paradigm but the underlying molecular mechanisms about the toxicity of ZnO-np remain unclear. This study was done to determine the potential toxicity of ZnO-np and to assess the toxicity mechanism in normal skin cells. Synthesized ZnO-np generated reactive oxygen species (ROS), as determined by electron spin resonance. After uptake into cells, ZnO-np induced ROS in a concentration- and time-dependent manner. To demonstrate ZnO-np toxicity mechanism related to ROS, we detected abnormal autophagic vacuoles accumulation and mitochondria dysfunction after ZnO-np treatment. Furthermore mitochondria membrane potential and adenosine-5′-triphosphate (ATP) production are decreased for culture with ZnO-np. We conclude that ZnO-np leads to cell death through autophagic vacuole accumulation and mitochondria damage in normal skin cells via ROS induction. Accordingly, ZnO-np may cause toxicity and the results highlight and need for careful regulation of ZnO-np production and use.
This paper presents an analytical method for analyzing the electromagnetic performance of a superconducting (SC) machine according to the 10 MW shielding configuration and the presence or absence of ...an armature core. To establish the SC machine design process, an analytical method considers shielding conditions and armature core type is included. The presented analytical method derives the governing equations and general solutions for each region using Maxwell’s equations and electromagnetic field theory. Furthermore, it calculates the analytical solutions by applying appropriate boundary conditions. Additionally, the performance of actively and passively shielded, with the same size and shielding performance of SC machine is compared. The electromagnetic performance obtained through the analytical method is compared with finite element analysis to validate its accuracy. The accuracy of the presented analytical method can be utilized in various design analyzes, including initial design and optimal design.
Titanium dioxide (TiO2) nanoparticles are widely used in cosmetics, sunscreen, electronics, drug delivery systems, and diverse bio-application fields. In the workplace, the primary exposure route for ...TiO2 nanoparticles is inhalation through the respiratory system. Because TiO2 nanoparticles have different physiological properties, in terms of size and bioactivity, their toxic effects in the respiratory system must be determined. In this study, to determine the toxic effect of inhaled TiO2 nanoparticles in the lung and the underlying mechanism, we used a whole-body chamber inhalation system to expose A/J mice to TiO2 nanoparticles for 28 days. During the experiments, the inhaled TiO2 nanoparticles were characterized using a cascade impactor and transmission electron microscopy. After inhalation of the TiO2 nanoparticles, hyperplasia and inflammation were observed in a TiO2 dose-dependent manner. To determine the biological mechanism of the toxic response in the lung, we examined endoplasmic reticulum (ER) and mitochondria in lung. The ER and mitochondria were disrupted and dysfunctional in the TiO2-exposed lung leading to abnormal autophagy. In summary, we assessed the potential risk of TiO2 nanoparticles in the respiratory system, which contributed to our understanding of the mechanism underlining TiO2 nanoparticle toxicity in the lung.
•Inhalation of TiO2 nanoparticles leads to inflammatory response in lungs.•Inhalation of TiO2 nanoparticles activates ER stress.•Inhalation of TiO2 nanoparticles effects to autophagy accumulation.
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