Influence of Double-Pulse Electrodeposition Parameters on the Performance of Ag/AgCl Electrochemical Electrode for Marine Electric Field.

This paper describes a Ag/AgCl electrochemical electrode for marine electric field measurements, which was prepared by depositing silver chloride on a silver foil substrate using double-pulse electrodeposition. The impact of positive direction peak current density and deposition time on electrode performance in the preparation of Ag/AgCl electrodes through double-pulse electrodeposition was investigated. Scanning electron microscopy and voltammetry have been used to study the properties of the prepared electrodes. This work reveals the correlation between the electrochemical behavior of electrodes and the physical properties of their surfaces, especially specific surface area and porosity. The study verified the characteristics of Ag/AgCl marine electric field electrodes obtained with different pulse parameters by analyzing the potential stability and noise level of the electrode in salt water. The study's results have positive significance for improving the accuracy of marine electric field measurements.

Mandating indoor air quality for public buildings.

If some countries lead by example, standards may increasingly become normalized.

In vivo characterization of glycogen storage disease type III in a mouse model using glycoNOE MRI.

PURPOSE: Glycogen storage disease type III (GSD III) is a rare inherited metabolic disease characterized by excessive accumulation of glycogen in liver, skeletal muscle, and heart. Currently, there are no widely available noninvasive methods to assess tissue glycogen levels and disease load. Here, we use glycogen nuclear Overhauser effect (glycoNOE) MRI to quantify hepatic glycogen levels in a mouse model of GSD III. METHODS: Agl knockout mice (n = 13) and wild-type controls (n = 10) were scanned for liver glycogen content using glycoNOE MRI. All mice were fasted for 12 to 16 h before MRI scans. GlycoNOE signal was quantified by fitting the Z-spectrum using a four-pool Voigt lineshape model. Next, the fitted direct water saturation pool was removed and glycoNOE signal was estimated from the integral of the residual Z spectrum within -0.6 to -1.4 ppm. Glycogen concentration was also measured ex vivo using a biochemical assay. RESULTS: GlycoNOE MRI clearly distinguished Agl knockout mice from wild-type controls, showing a statistically significant difference in glycoNOE signals in the livers across genotypes. There was a linear correlation between glycoNOE signal and glycogen concentration determined by the biochemical assay. The obtained glycoNOE maps of mouse livers also showed higher glycogen levels in Agl knockout mice compared to wild-type mice. CONCLUSION: GlycoNOE MRI was used successfully as a noninvasive method to detect liver glycogen levels in mice, suggesting the potential of this method to be applied to assess glycogen storage diseases.

Relative Role of Age Groups and Indoor Environments in Influenza Transmission Under Different Urbanization Rates in China.

Exploring the relative role of different indoor environments in respiratory infections transmission remains unclear, which is crucial for developing targeted nonpharmaceutical interventions. In this study, a total of 2,583,441 influenza-like illness cases tested from 2010 to 2017 in China were identified. An agent-based model was built and calibrated with the surveillance data, to assess the roles of 3 age groups (children <19 years, younger adults 19-60 years, older adults >60 years) and 4 types of indoor environments (home, schools, workplaces, and community areas) in influenza transmission by province with varying urbanization rates. When the urbanization rates increased from 35% to 90%, the proportion of children aged <19 years among influenza cases decreased from 76% to 45%. Additionally, we estimated that infections originating from children decreased from 95.1% (95% confidence interval (CI): 92.7, 97.5) to 59.3% (95% CI: 49.8, 68.7). Influenza transmission in schools decreased from 80.4% (95% CI: 76.5, 84.3) to 36.6% (95% CI: 20.6, 52.5), while transmission in the community increased from 2.4% (95% CI: 1.9, 2.8) to 45.4% (95% CI: 35.9, 54.8). With increasing urbanization rates, community areas and younger adults contributed more to infection transmission. These findings could help the development of targeted public health policies. This article is part of a Special Collection on Environmental Epidemiology. This article is part of a Special Collection on Environmental Epidemiology.

Risk evaluation of venue types and human behaviors of COVID-19 outbreaks in public indoor environments: A systematic review and meta-analysis.

Despite increasing vaccination rates, the incidence of breakthrough infections with COVID-19 has increased due to the continued emergence of new variants of the SARS-CoV-2 coronavirus. Therefore, Non-pharmaceutical interventions remain the most effective measures for coping with the ever-changing pandemic. The lifting of compulsory interventions has made individuals primary responsibility for their own health, which highlights the importance of increasing awareness of the infection risk from the environment in which they live and their individual behaviors. We systematically searched PubMed, Web of Science, ScienceDirect, and Scopus on April 17, 2023, for all studies reporting COVID-19 outbreaks in public indoor venues. The study outcome was the attack rate. A total of 42 studies, which included cross-sectional studies, cohort studies, and case studies, reporting data on 1951 confirmed cases in 64 COVID-19 outbreaks satisfied the meta-analysis and were included in the review. A random-effect model was used in the meta-analysis, and subgroup analyses were conducted to investigate factors affecting attack rates. We found a strong level of evidence (p < 0.01) supporting a higher pooled attack rate in recreation-related venues (0.44, 95% CI: 0.30 to 0.60) than in work-related venues (0.21, 95% CI: 0.16 to 0.27). Compared to those outbreaks without that, outbreaks with high-intensity exercise, vocalization, contact behavior, or close body proximity had a higher attack rate of 0.51, 0.55, 0.33, and 0.39, respectively. Further studies suggest that different attack rates across different types of settings may be the result of heterogeneity in exposed people's behaviors. There were significant heterogeneities that may limit the interpretation of connections between influencing factors and outbreak outcomes. The identification of key behaviors that may contribute to transmission risk, and their correlation with venue type, has important implications for the development of future public health interventions and individual prevention strategies for respiratory infectious diseases such as COVID-19.

Creatine mapping of the brain at 3T by CEST MRI.

PURPOSE: To assess the feasibility of CEST-based creatine (Cr) mapping in brain at 3T using the guanidino (Guan) proton resonance. METHODS: Wild type and knockout mice with guanidinoacetate N-methyltransferase deficiency and low Cr and phosphocreatine (PCr) concentrations in the brain were used to assign the Cr and protein-based arginine contributions to the GuanCEST signal at 2.0 ppm. To quantify the Cr proton exchange rate, two-step Bloch-McConnell fitting was used to fit the extracted CrCEST line-shape and multi-B1 Z-spectral data. The pH response of GuanCEST was simulated to demonstrate its potential for pH mapping. RESULTS: Brain Z-spectra of wild type and guanidinoacetate N-methyltransferase deficiency mice show a clear Guan proton peak at 2.0 ppm at 3T. The CrCEST signal contributes ∼23% to the GuanCEST signal at B1 = 0.8 µT, where a maximum CrCEST effect of 0.007 was detected. An exchange rate range of 200-300 s-1 was estimated for the Cr Guan protons. As revealed by the simulation, an elevated GuanCEST in the brain is observed when B1 is less than 0.4 µT at 3T, when intracellular pH reduces by 0.2. Conversely, the GuanCEST decreases when B1 is greater than 0.4 µT with the same pH drop. CONCLUSIONS: CrCEST mapping is possible at 3T, which has potential for detecting intracellular pH and Cr concentration in brain.

Urban surface classification using semi-supervised domain adaptive deep learning models and its application in urban environment studies.

High-resolution urban surface information, e.g., the fraction of impervious/pervious surface, is pivotal in studies of local thermal/wind environments and air pollution. In this study, we introduced and validated a domain adaptive land cover classification model, to automatically classify Google Earth images into pixel-based land cover maps. By combining domain adaptation (DA) and semi-supervised learning (SSL) techniques, our model demonstrates its effectiveness even when trained with a limited dataset derived from Gaofen2 (GF2) satellite images. The model's overall accuracy on the translated GF2 dataset improved significantly from 19.5% to 75.2%, and on the Google Earth image dataset from 23.1% to 61.5%. The overall accuracy is 2.9% and 3.4% higher than when using only DA. Furthermore, with this model, we derived land cover maps and investigated the impact of land surface composition on the local meteorological parameters and air pollutant concentrations in the three most developed urban agglomerations in China, i.e., Beijing, Shanghai and the Great Bay Area (GBA). Our correlation analysis reveals that air temperature exhibits a strong positive correlation with neighboring artificial impervious surfaces, with Pearson correlation coefficients higher than 0.6 in all areas except during the spring in the GBA. However, the correlation between air pollutants and land surface composition is notably weaker and more variable. The primary contribution of this paper is to provide an efficient method for urban land cover extraction which will be of great value for assessing the urban surface composition, quantifying the impact of land use/land cover, and facilitating the development of informed policies.

Effect of Rapid Urbanization in Mainland China on the Seasonal Influenza Epidemic: Spatiotemporal Analysis of Surveillance Data From 2010 to 2017.

BACKGROUND: The world is undergoing an unprecedented wave of urbanization. However, the effect of rapid urbanization during the early or middle stages of urbanization on seasonal influenza transmission remains unknown. Since about 70% of the world population live in low-income countries, exploring the impact of urbanization on influenza transmission in urbanized countries is significant for global infection prediction and prevention. OBJECTIVE: The aim of this study was to explore the effect of rapid urbanization on influenza transmission in China. METHODS: We performed spatiotemporal analyses of province-level influenza surveillance data collected in Mainland China from April 1, 2010, to March 31, 2017. An agent-based model based on hourly human contact-related behaviors was built to simulate the influenza transmission dynamics and to explore the potential mechanism of the impact of urbanization on influenza transmission. RESULTS: We observed persistent differences in the influenza epidemic attack rates among the provinces of Mainland China across the 7-year study period, and the attack rate in the winter waves exhibited a U-shaped relationship with the urbanization rates, with a turning point at 50%-60% urbanization across Mainland China. Rapid Chinese urbanization has led to increases in the urban population density and percentage of the workforce but decreases in household size and the percentage of student population. The net effect of increased influenza transmission in the community and workplaces but decreased transmission in households and schools yielded the observed U-shaped relationship. CONCLUSIONS: Our results highlight the complicated effects of urbanization on the seasonal influenza epidemic in China. As the current urbanization rate in China is approximately 59%, further urbanization with no relevant interventions suggests a worrisome increasing future trend in the influenza epidemic attack rate.

Ginsenoside compound K alleviates osteoarthritis by inhibiting NLRP3­mediated pyroptosis.

Ginsenoside compound K (GCK) has been previously reported to be a potent antiarthritic and bone-protective agent. Therefore, the present study aimed to explore the potential effects of GCK on osteoarthritis and its regulatory effects on the pyroptosis of chondrocytes. Primary mouse chondrocytes (PMCs) were used for in vitro analysis. ELISA assays revealed that compared with the untreated cells, TNF-α induced a significant increase in IL-6, MMP13, A disintegrin and metalloproteinase with thrombospondin motifs 5 and MMP3 expression but induced a significant decrease in aggrecan and collagen II expression. By contrast, GCK reversed the aforementioned alterations in a dose-dependent manner. Experimental osteoarthritis was subsequently induced in mice through transection of the medial meniscotibial ligament and medial collateral ligament in the right knee [destabilization of the medial meniscus (DMM) mice]. GCK was found to reduce cartilage degradation in vivo in DMM mice, which was assessed using the Osteoarthritis Research Society International (OARSI) score, collagen II and MMP13 expression. Cartilage degradation is associated with higher OARSI score, decreased collagen II and increased MMP13 expression. In PMCs, TNF-α treatment stimulated an increase in the expression of NLR family pyrin domain containing 3 (NLRP3), Gasdermin D-N terminal (GSDMD-NT), cleaved caspase-1 and mature IL-1ß, markers that indicate the occurrence of pyroptosis. However, GCK treatment suppressed the increase of the aforementioned proteins in a dose-dependent manner. Immunohistochemistry staining of the knee joint tissue sections from the DMM mice confirmed that GCK attenuated the NLRP3 and GSDMD-NT expression that was induced by DMM surgery. In conclusion, the present study revealed that GCK can reduce cartilage degradation in an osteoarthritis model by inhibiting the NLRP3-inflammasome activation and subsequent pyroptosis.

Close contact behaviors of university and school students in 10 indoor environments.

Close contact routes, including short-range airborne and large-droplet routes, play an important role in the transmission of SARS-CoV-2 in indoor environments. However, the exposure risk of such routes is difficult to quantify due to the lack of data on the close contact behavior of individuals. In this study, a digital wearable device, based on semi-supervised learning, was developed to automatically record human close contact behavior. We collected 337,056 s of indoor close contact of school and university students from 194.5 h of depth video recordings in 10 types of indoor environments. The correlation between aerosol exposure and close contact behaviors was then evaluated. Individuals in restaurants had the highest close contact ratio (64%), as well as the highest probability of face-to-face pattern (78%) during close contact. Accordingly, university students showed greater exposure potential in dormitories than school students in homes, however, a lower exposure was observed in classrooms and postgraduate student offices in comparison with school students in classrooms. In addition, restaurants had the highest aerosol exposure volume for both short-range inhalation and direct deposition on the facial mucosa. Thus, the classroom was established as the primary indoor environment where school students are exposed to aerosols.

Bloch simulator-driven deep recurrent neural network for magnetization transfer contrast MR fingerprinting and CEST imaging.

PURPOSE: To develop a unified deep-learning framework by combining an ultrafast Bloch simulator and a semisolid macromolecular magnetization transfer contrast (MTC) MR fingerprinting (MRF) reconstruction for estimation of MTC effects. METHODS: The Bloch simulator and MRF reconstruction architectures were designed with recurrent neural networks and convolutional neural networks, evaluated with numerical phantoms with known ground truths and cross-linked bovine serum albumin phantoms, and demonstrated in the brain of healthy volunteers at 3 T. In addition, the inherent magnetization-transfer ratio asymmetry effect was evaluated in MTC-MRF, CEST, and relayed nuclear Overhauser enhancement imaging. A test-retest study was performed to evaluate the repeatability of MTC parameters, CEST, and relayed nuclear Overhauser enhancement signals estimated by the unified deep-learning framework. RESULTS: Compared with a conventional Bloch simulation, the deep Bloch simulator for generation of the MTC-MRF dictionary or a training data set reduced the computation time by 181-fold, without compromising MRF profile accuracy. The recurrent neural network-based MRF reconstruction outperformed existing methods in terms of reconstruction accuracy and noise robustness. Using the proposed MTC-MRF framework for tissue-parameter quantification, the test-retest study showed a high degree of repeatability in which the coefficients of variance were less than 7% for all tissue parameters. CONCLUSION: Bloch simulator-driven, deep-learning MTC-MRF can provide robust and repeatable multiple-tissue parameter quantification in a clinically feasible scan time on a 3T scanner.

Comparative analysis of inflight transmission of SARS-CoV-2, influenza, and SARS-CoV-1.

The aim of this study is to evaluate the infection risk of aircraft passengers seated within and beyond two rows of the index case(s) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A(H1N1)pdm09 virus, and SARS-CoV-1. PubMed databases were searched for articles containing information on air travel-related transmission of SARS-CoV-2, influenza A(H1N1)pdm09 virus, and SARS-CoV-1 infections. We performed a meta-analysis of inflight infection data. In the eight flights where the attack rate could be calculated, the inflight SARS-CoV-2 attack rates ranged from 2.6% to 16.1%. The risk ratios of infection for passengers seated within and outside the two rows of the index cases were 5.64 (95% confidence interval (CI):1.94-16.40) in SARS-CoV-2 outbreaks, 4.26 (95% CI:1.08-16.81) in the influenza A(H1N1)pdm09 virus outbreaks, and 1.91 (95% CI:0.80-4.55) in SARS-CoV-1 outbreaks. Furthermore, we found no significant difference between the attack rates of SARS-CoV-2 in flights where the passengers were wearing masks and those where they were not (p = 0.22). The spatial distribution of inflight SARS-CoV-2 outbreaks was more similar to that of the influenza A(H1N1)pdm09 virus outbreaks than to that of SARS-CoV-1. Given the high proportion of asymptomatic or pre-symptomatic infection in SARS-CoV-2 transmission, we hypothesised that the proximity transmission, especially short-range airborne route, might play an important role in the inflight SARS-CoV-2 transmission.

Risk of air and surface contamination during application of different noninvasive respiratory support for patients with COVID-19.

OBJECTIVES: We compared the risk of environmental contamination among patients with COVID-19 who received high-flow nasal cannula (HFNC), noninvasive ventilation (NIV), and conventional oxygen therapy (COT) via nasal cannula for respiratory failure. METHODS: Air was sampled from the hospital isolation rooms with 12 air changes/hr where 26 patients with COVID-19 received HFNC (up to 60 l/min, n = 6), NIV (n = 6), or COT (up to 5 l/min of oxygen, n = 14). Surface samples were collected from 16 patients during air sampling. RESULTS: Viral RNA was detected at comparable frequency in air samples collected from patients receiving HFNC (3/54, 5.6%), NIV (1/54, 1.9%), and COT (4/117, 3.4%) (P = 0.579). Similarly, the risk of surface contamination was comparable among patients receiving HFNC (3/46, 6.5%), NIV (14/72, 19.4%), and COT (8/59, 13.6%) (P = 0.143). An increment in the cyclic thresholds of the upper respiratory specimen prior to air sampling was associated with a reduced SARS-CoV-2 detection risk in air (odds ratio 0.83 [95% confidence interval 0.69-0.96], P = 0.027) by univariate logistic regression. CONCLUSION: No increased risk of environmental contamination in the isolation rooms was observed in the use of HFNC and NIV vs COT among patients with COVID-19 with respiratory failure. Higher viral load in the respiratory samples was associated with positive air samples.

Student close contact behavior and COVID-19 transmission in China's classrooms.

Classrooms are high-risk indoor environments, so analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in classrooms is important for determining optimal interventions. Due to the absence of human behavior data, it is challenging to accurately determine virus exposure in classrooms. A wearable device for close contact behavior detection was developed, and we recorded >250,000 data points of close contact behaviors of students from grades 1 to 12. Combined with a survey on students' behaviors, we analyzed virus transmission in classrooms. Close contact rates for students were 37 ± 11% during classes and 48 ± 13% during breaks. Students in lower grades had higher close contact rates and virus transmission potential. The long-range airborne transmission route is dominant, accounting for 90 ± 3.6% and 75 ± 7.7% with and without mask wearing, respectively. During breaks, the short-range airborne route became more important, contributing 48 ± 3.1% in grades 1 to 9 (without wearing masks). Ventilation alone cannot always meet the demands of COVID-19 control; 30 m3/h/person is suggested as the threshold outdoor air ventilation rate in a classroom. This study provides scientific support for COVID-19 prevention and control in classrooms, and our proposed human behavior detection and analysis methods offer a powerful tool to understand virus transmission characteristics and can be employed in various indoor environments.

Toward accurate cerebral blood flow estimation in mice after accounting for anesthesia.

Purpose: To improve the accuracy of cerebral blood flow (CBF) measurement in mice by accounting for the anesthesia effects. Methods: The dependence of CBF on anesthesia dose and time was investigated by simultaneously measuring respiration rate (RR) and heart rate (HR) under four different anesthetic regimens. Quantitative CBF was measured by a phase-contrast (PC) MRI technique. RR was evaluated with a mouse monitoring system (MouseOX) while HR was determined using an ultrashort-TE MRI sequence. CBF, RR, and HR were recorded dynamically with a temporal resolution of 1 min in a total of 19 mice. Linear regression models were used to investigate the relationships among CBF, anesthesia dose, RR, and HR. Results: CBF, RR, and HR all showed a significant dependence on anesthesia dose (p < 0.0001). However, the dose in itself was insufficient to account for the variations in physiological parameters, in that they showed a time-dependent change even for a constant dose. RR and HR together can explain 52.6% of the variations in CBF measurements, which is greater than the amount of variance explained by anesthesia dose (32.4%). Based on the multi-parametric regression results, a model was proposed to correct the anesthesia effects in mouse CBF measurements, specifically C B F c o r r e c t e d = C B F + 0.58 R R - 0.41 H R - 32.66 D o s e . We also reported awake-state CBF in mice to be 142.0 ± 8.8 mL/100 g/min, which is consistent with the model-predicted value. Conclusion: The accuracy of CBF measurement in mice can be improved by using a correction model that accounts for respiration rate, heart rate, and anesthesia dose.

Interrogation of dynamic glucose-enhanced MRI and fluorescence-based imaging reveals a perturbed glymphatic network in Huntington's disease.

Huntington's disease (HD) is a neurodegenerative disorder that presents with progressive motor, mental, and cognitive impairment leading to early disability and mortality. The accumulation of mutant huntingtin protein aggregates in neurons is a pathological hallmark of HD. The glymphatic system, a brain-wide perivascular network, facilitates the exchange of interstitial fluid (ISF) and cerebrospinal fluid (CSF), supporting interstitial solute clearance including abnormal proteins from mammalian brains. In this study, we employed dynamic glucose-enhanced (DGE) MRI to measure D-glucose clearance from CSF as a tool to assess CSF clearance capacity to predict glymphatic function in a mouse model of HD. Our results demonstrate significantly diminished CSF clearance efficiency in premanifest zQ175 HD mice. The impairment of CSF clearance of D-glucose, measured by DGE MRI, worsened with disease progression. These DGE MRI findings in compromised glymphatic function in HD mice were further confirmed with fluorescence-based imaging of glymphatic CSF tracer influx, suggesting an impaired glymphatic function in premanifest stage of HD. Moreover, expression of the astroglial water channel aquaporin-4 (AQP4) in the perivascular compartment, a key mediator of glymphatic function, was significantly diminished in both HD mouse brain as well as postmortem human HD brain. Our data, acquired using a clinically translatable MRI approach, indicate a perturbed glymphatic network in the HD brain as early as in the premanifest stage. Further validation of these findings in clinical studies should provide insights into potential of glymphatic clearance as a HD biomarker and for glymphatic functioning as a disease-modifying therapeutic target for HD.

The exchange rate of creatine CEST in mouse brain.

PURPOSE: To estimate the exchange rate of creatine (Cr) CEST and to evaluate the pH sensitivity of guanidinium (Guan) CEST in the mouse brain. METHODS: Polynomial and Lorentzian line-shape fitting (PLOF) were implemented to extract the amine, amide, and Guan CEST signals from the brain Z-spectrum at 11.7T. Wild-type (WT) and knockout mice with the guanidinoacetate N-methyltransferase deficiency (GAMT-/- ) that have low Cr and phosphocreatine (PCr) concentrations in the brain were used to extract the CrCEST signal. To quantify the CrCEST exchange rate, a two-step Bloch-McConnell (BM) fitting was used to fit the CrCEST line-shape, B1 -dependent CrCEST, and the pH response with different B1 values. The pH in the brain cells was altered by hypercapnia to measure the pH sensitivity of GuanCEST. RESULTS: Comparison between the Z-spectra of WT and GAMT-/- mice suggest that the CrCEST is between 20% and 25% of the GuanCEST in the Z-spectrum at 1.95 ppm between B1 = 0.8 and 2 µT. The CrCEST exchange rate was found to be around 240-480 s-1 in the mouse brain, which is significantly lower than that in solutions (∼1000 s-1 ). The hypercapnia study on the mouse brain revealed that CrCEST at B1 = 2 µT and amineCEST at B1 = 0.8 µT are highly sensitive to pH change in the WT mouse brain. CONCLUSIONS: The in vivo CrCEST exchange rate is slow, and the acquisition parameters for the CrCEST should be adjusted accordingly. CrCEST is the major contribution to the opposite pH-dependence of GuanCEST signal under different conditions of B1 in the brain.

Feasibility and accuracy of coronary artery calcium score on virtual non-contrast images derived from a dual-layer spectral detector CT: A retrospective multicenter study.

Rationale and objective: This retrospective study was to evaluate the feasibility and accuracy of coronary artery calcium score (CACS) from virtual non-contrast (VNC) images in comparison with that from true non-contrast (TNC) images. Materials and methods: A total of 540 patients with suspected of coronary artery disease (CAD) who underwent a dual-layer spectral detector CT (SDCT) in three hospitals were eligible for this study and 233 patients were retrospectively enrolled for further analysis. The CACS was calculated from both TNC and VNC images and compared. Linear regression analysis of the CACS was performed between TNC and VNC images. Results: The correlation of overall CACS from VNC and TNC images was very strong (r = 0.923, p < 0.001). The CACS from VNC images were lower than that from TNC images (221 versus. 69, p < 0.001). When the regression equation of the overall coronary artery was applied, the mean calibrated CACS-VNC was 221 which had a significant difference from the CACS-TNC (p = 0.017). When the regression equation of each coronary branch artery was applied, the mean calibrated CACS-VNC was 221, which had a significant difference from the CACS-TNC (p = 0.003). But the mean difference between the CACS-TNC and the calibrated CACS-VNC in either way was less than 1. The agreement on risk stratification with CACS-TNC and CCACS-VNC was almost perfect. Conclusion: This multicenter study with dual-layer spectral detector CT showed that it was feasible to calculate CACS from the VNC images derived from the spectral coronary artery CT angiography scan, and the results were in good accordance with the TNC images after correction. Therefore, the TNC scan could be omitted, reducing the radiation dose to patients and saving examination time while using dual-layer spectral detector CT.

Particle Deposition in Large-Scale Human Tracheobronchial Airways Predicted by Single-Path Modelling.

The health effects of particles are directly related to their deposition patterns (deposition site and amount) in human airways. However, estimating the particle trajectory in a large-scale human lung airway model is still a challenge. In this work, a truncated single-path, large-scale human airway model (G3-G10) with a stochastically coupled boundary method were employed to investigate the particle trajectory and the roles of their deposition mechanisms. The deposition patterns of particles with diameters (dp) of 1-10 µm are investigated under various inlet Reynolds numbers (Re = 100-2000). Inertial impaction, gravitational sedimentation, and combined mechanism were considered. With the increasing airway generations, the deposition of smaller particles (dp < 4 µm) increased due to gravitational sedimentation, while that of larger particles decreased due to inertial impaction. The obtained formulas of Stokes number and Re can predict the deposition efficiency due to the combined mechanism in the present model, and the prediction can be used to assess the dose-effect of atmospheric aerosols on the human body. Diseases in deeper generations are mainly attributed to the deposition of smaller particles under lower inhalation rates, while diseases at the proximal generations mainly result from the deposition of larger particles under higher inhalation rates.