Intracranial Seeding Following Surgery and Chemotherapy in a Child with a Spinal Cord Endodermal Sinus Tumor: A Case Report.

We herein report a case of an extremely rare spinal cord endodermal sinus tumor (EST). A nine-year-old boy presented with progressive paraparesis, hypesthesia, and urinary retention. Gadolinium-enhanced magnetic resonance imaging (MRI) revealed multiple intradural enhancing lesions at T1 to T9 without evidence of intracranial tumors. He underwent partial resection of the lesions, and histology revealed an EST. He received chemotherapy, but 12 months after surgery, rapid tumor progression and intracranial metastases with obstructive hydrocephalus were detected. Following external ventricular drainage, the patient's condition rapidly deteriorated, and he ultimately died. EST should be considered when confronting a homogenously enhancing intradural tumor of the spine on post-contrast MRI.

A machine learning model for predicting PM2.5 and nitrate concentrations based on long-term water-soluble inorganic salts datasets at a road site station.

In this study, long-term variations in the concentrations of PM2.5, water-soluble inorganic salts (WIS), and gaseous precursors measured by a roadside air quality monitoring station were investigated from 2017 to February 2021 to examine the formation mechanism of secondary inorganic PM2.5. A new machine learning model using WIS data as input variables was further developed to predict PM2.5 and nitrate concentrations for source tracing and effective control strategy development. The results showed that a reduction in the NOx concentration under VOC-limited O3 formation regime could offset the consumption of OH and O3, causing an increase in secondary NO3- and PM2.5 formation during fall and winter seasons. A good agreement was obtained between the predicted and measured PM2.5 values, with R2, root mean square error (RMSE), and mean absolute error (MAE) values of 0.81, 6.81 µg/m3, and 5.10 µg/m3, respectively. The nitrate ([NO3-]) prediction model could predict ∼59% of the atmospheric nitrate concentration. The sensitivity analysis of the input variables in the present model further revealed that NO3- and VOC were two important pollutants dominating the variation trend of PM2.5. It is recommended that decision makers should focus more on the reduction of VOC and O3 to reduce secondary PM2.5 formation during winter in central Taiwan. Real-time measurements of the chemical composition of PM2.5, taken as the regulatory air quality monitoring items are needed in the future.

WRF modeling of PM2.5 remediation by SALSCS and its clean air flow over Beijing terrain.

Atmospheric simulations were carried out over the terrain of entire Beijing, China, to investigate the effectiveness of an air-pollution cleaning system named Solar-Assisted Large-Scale Cleaning System (SALSCS) for PM2.5 mitigation by using the Weather Research and Forecasting (WRF) model. SALSCS was proposed to utilize solar energy to generate airflow therefrom the airborne particulate pollution of atmosphere was separated by filtration elements. Our model used a derived tendency term in the potential temperature equation to simulate the buoyancy effect of SALSCS created with solar radiation on its nearby atmosphere. PM2.5 pollutant and SALSCS clean air were simulated in the model domain by passive tracer scalars. Simulation conditions with two system flow rates of 2.64 × 105 m3/s and 3.80 × 105 m3/s were tested for seven air pollution episodes of Beijing during the winters of 2015-2017. The numerical results showed that with eight SALSCSs installed along the 6th Ring Road of the city, 11.2% and 14.6% of PM2.5 concentrations were reduced under the two flow-rate simulation conditions, respectively.

Aerosol Emission Monitoring and Assessment of Potential Exposure to Multi-walled Carbon Nanotubes in the Manufacture of Polymer Nanocomposites.

Recent animal studies have shown that carbon nanotubes (CNTs) may pose a significant health risk to those exposed in the workplace. To further understand this potential risk, effort must be taken to measure the occupational exposure to CNTs. Results from an assessment of potential exposure to multi-walled carbon nanotubes (MWCNTs) conducted at an industrial facility where polymer nanocomposites were manufactured by an extrusion process are presented. Exposure to MWCNTs was quantified by the thermal-optical analysis for elemental carbon (EC) of respirable dust collected by personal sampling. All personal respirable samples collected (n = 8) had estimated 8-h time weighted average (TWA) EC concentrations below the limit of detection for the analysis which was about one-half of the recommended exposure limit for CNTs, 1 µg EC/m(3) as an 8-h TWA respirable mass concentration. Potential exposure sources were identified and characterized by direct-reading instruments and area sampling. Area samples analyzed for EC yielded quantifiable mass concentrations inside an enclosure where unbound MWCNTs were handled and near a pelletizer where nanocomposite was cut, while those analyzed by electron microscopy detected the presence of MWCNTs at six locations throughout the facility. Through size selective area sampling it was identified that the airborne MWCNTs present in the workplace were in the form of large agglomerates. This was confirmed by electron microscopy where most of the MWCNT structures observed were in the form of micrometer-sized ropey agglomerates. However, a small fraction of single, free MWCNTs was also observed. It was found that the high number concentrations of nanoparticles, ~200000 particles/cm(3), present in the manufacturing facility were likely attributable to polymer fumes produced in the extrusion process.

Novel active personal nanoparticle sampler for the exposure assessment of nanoparticles in workplaces.

A novel active personal nanoparticle sampler (PENS), which enables the collection of both respirable particulate mass (RPM) and nanoparticles (NPs) simultaneously, was developed to meet the critical demand for personal sampling of engineered nanomaterials (ENMs) in workplaces. The PENS consists of a respirable cyclone and a micro-orifice impactor with the cutoff aerodynamic diameter (d(pa50)) of 4 µm and 100 nm, respectively. The micro-orifice impactor has a fixed micro-orifice plate (137 nozzles of 55 µm in the inner diameter) and a rotating, silicone oil-coated Teflon filter substrate at 1 rpm to achieve a uniform particle deposition and avoid solid particle bounce. A final filter is used after the impactor to collect the NPs. Calibration results show that the d(pa50) of the respirable cyclone and the micro-orifice impactor are 3.92 ± 0.22 µm and 101.4 ± 0.1 nm, respectively. The d(pa50) at the loaded micro-Al(2)O(3) mass of 0.36-3.18 mg is shifted to 102.9-101.2 nm, respectively, while it is shifted to 98.9-97.8 nm at the loaded nano-TiO(2) mass of 0.92-1.78 mg, respectively. That is, the shift of d(pa50) due to solid particle loading is small if the PENS is not overloaded. Both NPs and RPM concentrations were found to agree well with those of the IOSH respirable cyclone and MOUDI. By using the present PENS, the collected samples can be further analyzed for chemical species concentrations besides gravimetric analysis to determine the actual exposure concentrations of ENMs in both RPM and NPs fractions in workplaces, which are often influenced by the background or incident pollution sources.

Cholesteric liquid crystal devices with nanoparticle aggregation.

A broadband cholesteric liquid crystal (CLC) device with a multi-domain structure is demonstrated by using an aggregation of polyhedral oligomeric silsesquioxane (POSS) nanoparticles in the CLC layer. The aggregation pattern of the self-assembled POSS nanoparticles depends on the concentration of POSS doped in the mixture of POSS/CLC and the cooling rate of the mixture from a temperature higher than the clear point. POSS-induced changes in the bulk and surface properties of the cholesteric cells, such as a promotion of homeotropic alignment, help to form a cholesteric structure with a broadband reflection of light; the latter can be used for improvement of bistable CLC devices. A higher POSS concentration and a higher cooling rate both improve the appearance of the black-white CLC device.

Study of an axial flow cyclone to remove nanoparticles in vacuum.

An axial flow cyclone for removing nanoparticles was tested for collection efficiency. Data were validated numerically in vacuum conditions of several Torrs, with flow rates of 0.35-0.57 slpm. The experimental cutoff aerodynamic diameter of the cyclone ranged from 21.7 to 49.8 nm. A 3-D numerical simulation was conducted first to calculate detailed flow and pressure fields, then a Brownian Dynamics simulation was done to determine the collection efficiency of nanoparticles. Both centrifugal force and Brownian diffusion were taken into account. The simulated results for both pressure drop and cutoff aerodynamic diameter are in good agreement with the experimental data. In comparison, previous theories using simplified tangential flow field assumption are not able to predict collection efficiencies accurately. The numerical model developed in this study can facilitate cyclone design to classify valuable nanopowders below a certain diameter, or to remove toxic nanoparticles from the vacuum exhaust of process chambers commonly used in high-tech industries.