Particle Counter Research Articles

Evaluation of AUTION EYE AI-4510 flow cell morphology analyzer for counting particles in urine.

We evaluated the performance of a novel flow cell morphology analyzer AUTION EYE AI-4510 for counting particles in urine. Analytical performance was assessed according to the EFLM European Urinalysis Guideline 2023. Trueness was compared by analyzing 1.012 fresh urine samples with the AUTION EYE AI-4510 (ARKRAY, Inc., Kyoto, Japan) against phase-contrast visual microscopy. Poisson statistics were utilized in assessment of imprecision of particle counts both with quality control material and patient specimens. Relative imprecision against theoretical Poisson imprecision, R(CV), was estimated to be 1.1 for red blood cells (RBC), 1.0 for white blood cells (WBC), 0.9 for squamous epithelial cells (SEC) and 1.1 for bacteria. The agreement with visual microscopy (Cohen's weighted kappa) was 0.93 for RBC, 0.95 for WBC, 0.90 for SEC, 0.79 for non-squamous epithelial cells (NSEC), 0.67 for combined casts, 0.90 for crystals and 0.88 for bacteria. No clinically significant bias was observed. Limits of quantitation at CV=30 % reached 4×106/L for RBC and 5×106/L for WBC. Differentiation of urinary crystals was improved as compared to previous data on digital cuvette imaging. The ARKRAY AUTION EYE AI-4510 provided a desirable imprecision, met the criteria for linearity, LoQ and carry-over, and showed an optimum comparison to visual microscopy for RBC, WBC, SEC and crystals as defined in the EFLM European Urinalysis Guideline 2023. The identification of kidney damage is recommended to be improved by using user-defined review rules. Performance of bacteria counting needs to be confirmed against urine bacterial cultures.

The role of homogenization cycles and Poloxamer 188 on the quality of mitochondria isolated for use in mitochondrial transplantation therapy

Mitochondrial transplantation (MTx) offers a promising therapeutic approach to mitigate mitochondrial dysfunction in conditions such as ischemia–reperfusion (IR) injury. The quality and viability of donor mitochondria are critical to MTx success, necessitating the optimization of isolation protocols. This study aimed to assess a rapid mitochondrial isolation method, examine the relationship between mitochondrial size and membrane potential, and evaluate the potential benefits of Poloxamer 188 (P-188) in improving mitochondrial quality during the isolation process. Mitochondria were isolated from pectoral muscle biopsies of adult male Sprague–Dawley rats using an automated homogenizer. MitoTracker Deep Red (MTDR) staining and flow cytometry were used to assess mitochondrial purity, while the JC-1 assay evaluated membrane potential. Mitochondrial size groups were compared for membrane potential differences. Homogenization frequency and P-188 supplementation (1 mM) were assessed for their effects on mitochondrial membrane potential and particle size, and particle counts. The rapid isolation method yielded mitochondria that retained sufficient membrane potential to be effectively inhibited by carbonyl cyanide 3-chlorophenylhydrazone (CCCP), a disruptor of mitochondrial membrane potential. Larger mitochondria exhibited significantly higher JC-1 ratios, indicating greater membrane potential. Excessive homogenization (10 cycles) reduced membrane potential compared to 3 cycles homogenization (P = 0.026). P-188 significantly increased the JC-1 ratio from 10.26 ± 2.57 to 33.78 ± 17.78 (P = 0.023). Particle size and count analysis revealed that 10 cycles homogenization significantly increased particle count compared to 3 cycles homogenization (P = 0.0001), but was associated with smaller particle sizes (P = 0.0031). The rapid mitochondrial isolation method produced viable mitochondria, with larger mitochondria exhibiting superior membrane potential. Reducing homogenization frequency and incorporating P-188 improved mitochondrial quality and preserved particle size. These strategies offer promising strategies for optimizing MTx protocols. Further refinement of these techniques is necessary for their clinical application in MTx therapy.

Deep Learning-Assisted Fluorescence Single-Particle Detection of Fumonisin B1 Powered by Entropy-Driven Catalysis and Argonaute.

Timely and accurate detection of trace mycotoxins in agricultural products and food is significant for ensuring food safety and public health. Herein, a deep learning-assisted and entropy-driven catalysis (EDC)-Argonaute powered fluorescence single-particle aptasensing platform was developed for ultrasensitive detection of fumonisin B1 (FB1) using single-stranded DNA modified with biotin and red fluorescence-encoded microspheres as a signal probe and streptavidin-conjugated magnetic beads as separation carriers. The binding of aptamer with FB1 releases the trigger sequence to mediate EDC cycle to produce numerous 5'-phosphorylated output sequences, which can be used as the guide DNA to activate downstream Thermus thermophilus Argonaute (TtAgo) for cleaving the signal probe, resulting in increased number of fluorescence microspheres remaining in the final reaction supernatant after magnetic separation. Subsequently, through fast and accurate counting of red bright particles in the captured confocal fluorescence images from the supernatant via a YOLOv9 deep learning model, the sensitive and specific detection of FB1 could be realized. This approach has a limit of detection (LOD) of 0.89 pg/mL with a linear range from 1 pg/mL to 100 ng/mL, and satisfactory recovery (87.2-113.5%) in real food samples indicates its practicality. The integration of the aptamer and EDC with TtAgo broadens the target range of Argonaute and enhances sensitivity. Furthermore, incorporating deep learning significantly improves the analytical efficiency of single-particle detection. This work provides a promising analytical strategy in biosensing and promotes the application of fluorescence single-particle detection in food safety monitoring.

Optical characteristics and formation mechanism of haze events in Qingdao, a coastal city in China

During the field campaign conducted in Qingdao, Shandong Province, from December 2019 to January 2020, six significant haze episodes occurred. To investigate the optical characteristics and formation mechanisms of haze in this region, we utilized an optical particle counter to measure the size distribution of aerosol particles. The results showed that the average Angström exponent value during the campaign was 1.45, indicating that fine particulate matter dominated. Additionally, the aerosol scattering coefficient, absorption coefficient, and single scattering albedo were measured using a cavity-attenuated phase shift instrument. It was observed that both scattering and extinction coefficients significantly increased during the haze episodes, while SSA notably decreased at the onset of haze, which may be related to newly emitted aerosol particles. Air quality monitors detected a marked increase in sulfur compounds and nitrogen oxides during the haze episodes, with nitrogen oxides being higher than sulfur compounds, indicating that local pollution was primarily driven by vehicular emissions. Using the HYSPLIT4 model, we analyzed atmospheric transport trajectories and found that regional transport played a critical role in haze events. Analysis of micropulse lidar data revealed that the boundary layer height during the haze episodes was significantly lower than during non-haze periods. The lower boundary layer height restricted pollutant dispersion, exacerbating pollution levels. High relative humidity also contributed to the hygroscopic growth of aerosols, altering atmospheric thermal balance and playing a crucial role in the formation of haze events.

Knock-out mouse models and single particle ICP-MS reveal that SP-D and SP-A deficiency reduces agglomeration of inhaled gold nanoparticles in vivo without significant changes to overall lung clearance

The role of surfactant proteins A and D (SP-A and SP-D) in lung clearance and translocation to secondary organs of inhaled nanoparticles was investigated by exposing SP-A and SP-D knockout (AKO and DKO) and wild type (WT) mice nose-only for 3 hours to an aerosol of 20 nm gold nanoparticles (AuNPs). Animals were euthanised at 0-, 1-, 7- and 28-days post-exposure. Analysis by inductively coupled plasma mass spectrometry (ICP-MS) of the liver and kidneys showed that extrapulmonary translocation was below the limits of detection. Imaging of the lungs by laser ablation ICP-MS confirmed the homogenous distribution of AuNPs. Coherent anti-Stokes Raman Scattering, Second Harmonic Generation and Two-Photon Fluorescence imaging were applied for semi-quantitative analysis of the uptake of AuNPs by alveolar macrophages and found uptake increased with time post-exposure, peaking after 7 days, and with the largest increase in uptake being in WT mice. Single particle ICP-MS allowed particle counting and sizing of AuNPs in the lungs showing that particle agglomeration following deposition within the lung was greater for the wildtype than the knockout models, indicating a role for SP-A and SP-D in agglomeration, however, any effect of this on overall lung clearance was minimal. For all groups, the Au (mass) lung burden initial clearance half-time was approximately 20–25 d, however, the AuNP (particle number) lung burden clearance half-time was shorter at approximately 10 days. In general terms, differences between the results for the three models were limited, indicating the preferential clearance of smaller particles from the lung.

One-Point Calibration of Low-Cost Sensors for Particulate Air Matter (PM) Concentration Measurement

The use of low-cost sensors has dramatically increased in recent years in all engineering sectors. In the buildings and automotive field, low-cost sensors open very interesting perspectives, because they allow one to monitor temperature and humidity distributions together with air quality in a widespread and punctual way and allow for the control of all energy parameters. The main issue remains the validation of the measurements. In this work, we propose an innovative approach to verify the measurements given by some low-cost systems built ad hoc for automotive applications. Two independent low-cost measurement systems were set to measure Particulate Air Matter (PM) concentration, TVOC concentration, CO2 concentration, formaldehyde concentration, air temperature, relative humidity, pressure, air flow velocity, and GPS position. These systems were calibrated for PM concentration measurement by comparison with standard and certified sensors used by the regional authority of the Emilia-Romagna region (ARPAE, Italy) for characterizing air quality. The duration of the analysis, three days, is not representative of the diverse environmental conditions that occur across different seasons. However, the innovation of this approach lies in both the in-field comparison of low-cost and high-quality sensors and the use of proper conversion approaches for mass concentration measurements. A quantitative analysis of the sensors’ performance is given, with a focus on the effects of time granularity, relative humidity, mass conversion from particle counts, and size detection response. The results show that the low-cost sensors’ measurements of air temperature, relative humidity, and particle number concentration are in good agreement with high-quality sensors’ measurements, with a strong impact of relative humidity on performance indicators. Overall, good quality and consistency of the data among the sensors were achieved.

Extracellular vesicles in ageing cold-stored whole blood may not compensate for the decreasing haemostatic function in vitro.

Extracellular vesicles (EVs) have procoagulative properties. As EVs are known to accumulate in stored blood products, we compared the EV content and coagulation capacity of leukoreduced cold-stored whole blood (CSWB) with current prehospital and in-hospital component therapies to understand the role of EVs in the haemostatic capacity of ageing CSWB. Blood was obtained from 12 O RhD-positive male donors. CSWB was compared with in-hospital component therapy of red blood cells (RBCs), OctaplasLG and buffy-coat platelets and prehospital component therapy of RBC and lyophilized plasma. Samples were drawn on Days 1 and 14 of CSWB and RBC cold storage. Blood count, haemolysis markers, rotational thromboelastometry, sonorheometry and thrombin generation were analysed. EVs were analysed using nanoparticle tracking analysis and cellular origin was determined using imaging flow cytometry. There was a trend towards increased production of both platelet and RBC-derived EVs during CSWB storage. Particle count increased during storage, whereas thrombin generation slowed down and in viscoelastic assays, clotting times prolonged, clot formation became impaired, and stiffness of the resulting clot decreased. Both platelet and RBC-derived EVs increased in number in CSWB during storage. This did not appear to compensate for the in vitro decreasing haemostatic capacity of ageing CSWB, suggesting EVs produced during storage may not have active procoagulative effects, but rather reflect the ageing of blood cells.

Exposure to Secondhand Cannabis Smoke Among Children

The degree that in-home cannabis smoking can be detected in the urine of resident children is unclear. Test association of in-home cannabis smoking with urinary cannabinoids in children living at home. This cross-sectional study used baseline data from Project Fresh Air, a 2012-2016 randomized clinical trial to reduce fine particulate matter levels. Eligible participants were recruited from households in San Diego County, California, with children under age 14 years and an adult tobacco smoker in residence. Children's urine samples were analyzed in 2022. In-home cannabis smoking, measured by: parent or guardian report of in-home cannabis smoking; number of daily nonspecific smoking events computed via an air particle count algorithm; and number of daily cannabis smoking events ascertained by residualization, adjusting for air nicotine, tobacco smoking, and other air particle generating or ventilating activities. Levels of the cannabis biomarker Δ9-tetrahydrocannabinol (THC) and its major metabolites, 11-hydroxy-Δ9-tetrahydrocannabinol and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol. Biomarker molar equivalents were summed to represent total THC equivalents (TTE) in urine. Logistic regression assessed whether in-home smoking was associated with cannabis biomarker detection. For children with detectable urinary cannabinoids, linear regression assessed in-home smoking association with quantity of urinary TTE. A total of 275 children were included in analysis (mean [SD] age, 3.6 [3.6] years; 144 male [52.4%]; 38 Black [13.8%], 132 Hispanic [48.0%], and 52 White [18.9%]). Twenty-nine households (10.6%) reported in-home cannabis smoking in the past 7 days; 75 children [27.3%] had detectable urinary cannabinoids. Odds of detectable TTE in children's urine were significantly higher in households with reported in-home cannabis smoking than households without (odds ratio [OR], 5.0; 95% CI, 2.4-10.4) and with each additional ascertained daily cannabis smoking event (OR, 2.5; 95% CI, 1.6-3.9). Although the point estimate for TTE levels was higher among children with detectable urinary cannabinoids and exposure to more daily cannabis smoking events (increase per event, 35.68%; 95% CI, -7.12% to 98.21%), the difference was not statistically significant. In this cross-sectional study, in-home cannabis smoking was associated with significantly increased odds of child exposure to cannabis smoke, as assessed by urinary cannabinoid biomarkers. As young children spend most of their time at home, reducing in-home cannabis smoking could substantially reduce their exposure to the toxic and carcinogenic chemicals found in cannabis smoke.

Three-Dimensional (3D) Printing in Non-Industrial Spaces: A Summary of Emissions Evaluations in 11 School Settings.

Additive manufacturing or 3-dimensional (3D) printing is an emerging technology with increasing prevalence in non-industrial settings such as university and school settings. However, printers are often located in spaces not designed for this purpose. 3D-printer use in 11 university and K-12 schools was evaluated by identifying emissions using area air sampling for volatile organic compounds (VOCs) and particle counting instruments (PCIs) measuring ultrafine particulate (UFP) and evaluating controls to reduce potential exposure. Ventilation in printer locations was also characterized. VOCs and UFP were identified during 3D printing. Best-practice recommendations were provided to school health and safety staff to protect users, including workers and students. Recommendations included installing and implementing engineering controls, administrative controls, and personal protective equipment (PPE) to minimize exposure to 3D printer emissions. School health and safety staff can translate findings and recommendations for these 11 evaluations to identify 3D-printing areas on their campuses and use principles of industrial hygiene to protect workers and students and prevent the movement of emissions. VOCs and UFP were detected during 3D printing. There were opportunities to improve health and safety practices and reduce potential exposure when using 3D printing technologies.

Long-Term Evaluation of Mid-Cost Optical Particle Counters for PM2.5 Monitoring in an Underground Subway Station: Insights from a 15-Month Study

Long-Term Evaluation of Mid-Cost Optical Particle Counters for PM2.5 Monitoring in an Underground Subway Station: Insights from a 15-Month Study

Investigation of Vertical Profiles of Particulate Matter and Meteorological Variables up to 2.5 km in Altitude Using a Drone-Based Monitoring System

In this study, a drone-based measurement system equipped with miniaturized optical and condensation particle counters was deployed to investigate the vertical distribution of particulate matter and meteorological variables up to 2.5 km in altitude. Measurements captured at various altitudes demonstrated notable vertical variations in particle concentration and significant correlations with meteorological factors, particularly relative humidity (RH). Near the surface, within a well-mixed boundary layer, particle concentrations remained stable despite RH changes, indicating both anthropogenic and natural influences. At higher altitudes, a clear positive relationship between RH and particle number concentration emerged, particularly for smaller particles, while temperature inversions and distinct wind patterns influenced aerosol dispersion. The unmanned aerial vehicle system’s robust performance, validated against standard meteorological tower data, underscores its potential for high-resolution atmospheric profiling. These insights are crucial for understanding particle behavior in diverse atmospheric layers and have implications for refining air quality monitoring and climate models. Future work should incorporate chemical analysis of aerosols to further expand these findings and assess their environmental impact.

Modeling the Nucleation and Growth of Lead Sulfate Particles on Lead Electrodes

Abstract Lead-acid batteries (LABs) play a pivotal role in the energy storage sector with applications spanning from starting-lighting-ignition batteries to grid energy storage. Passivation of lead negative electrodes by PbSO4 particles is a fundamental mechanism limiting the performance of LAB. In this regard, an electrochemical model is developed that simulates the nucleation and growth (N&G) dynamics of PbSO4 particles on a flat lead electrode, responsible for its passivation. The model considers the electrochemical reactions between lead electrode and sulfuric acid, N&G of PbSO4 particles, passivation of the lead surface, and the ternary transport of PbSO4 (aq), bisulfate, and protons in H2SO4 electrolyte. The model is validated with a dataset of cyclic voltammetry (CV) responses collected at several scan rates and H2SO4 concentrations. The model shows remarkable qualitative and quantitative agreement with the experimental data including CV peak features, discharge capacity, and particle size. The model was employed to explore key N&G quantities, such as supersaturation, nucleation rate, particle count, growth rate, particle size, and surface coverage, and to examine how their interactions influence electrode utilization. Parametric studies were also conducted to evaluate how scan rates and acid concentrations influence the previously mentioned N&G quantities and, subsequently, the utilization of the electrode.

Fast and sensitive measurements of sub-3 nm particles using Condensation Particle Counters For Atmospheric Rapid Measurements (CPC FARM)

Abstract. New particle formation (NPF) is the atmospheric process whereby gas molecules react and nucleate to form detectable particles. NPF has a strong impact on Earth's radiative balance as it produces roughly half of global cloud condensation nuclei. However, the time resolution and sensitivity of current instrumentation are inadequate in measuring the size distribution of sub-3 nm particles, the particles critical for understanding NPF. Here we present the Condensation Particle Counters For Atmospheric Rapid Measurements (CPC FARM), a method to measure the concentrations of freshly nucleated particles. The CPC FARM consists of five CPCs operating in parallel, each configured to operate at different detectable particle sizes between 1–3 nm. This study explores two methods to calculate the size distribution from the differential measurements across the CPC channels. The performance of both inversion methods was tested against the size distribution measured by a pair of stepping particle mobility sizers (SMPSs) during an ambient air sampling study in Pittsburgh, PA. Observational results indicate that the CPC FARM is more accurate with higher time resolution and sensitivity in the sub-3 nm range compared to the SMPS.

MicroVi: A Cost-Effective Microscopy Solution for Yeast Cell Detection and Count in Wine Value Chain.

In recent years, the wine industry has been researching how to improve wine quality along the production value chain. In this scenario, we present here a new tool, MicroVi, a cost-effective chip-sized microscopy solution to detect and count yeast cells in wine samples. We demonstrate that this novel microscopy setup is able to measure the same type of samples as an optical microscopy system, but with smaller size equipment and with automated cell count configuration. The technology relies on the top of state-of-the-art computer vision pipelines to post-process the images and count the cells. A typical pipeline consists of normalization, feature extraction (i.e., SIFT), image composition (to increase both resolution and scanning area), holographic reconstruction and particle count (i.e., Hough transform). MicroVi achieved a 2.19 µm resolution by properly resolving the G7.6 features from the USAF Resolving Power Test Target 1951. Additionally, we aimed for a successful calibration of cell counts for Saccharomyces cerevisiae. We compared our direct results with our current optical setup, achieving a linear calibration for measurements ranging from 0.5 to 50 million cells per milliliter. Furthermore, other yeast cells were qualitatively resolved with our MicroVi microscope, such as, Brettanomyces bruxellensis, or bacteria, like, Lactobacillus plantarum, thus confirming the system's reliability for consistent microbial assessment.

Quantifying the effect of particulate impurities on the ice nucleation behavior of pharmaceutical solutions.

Numerous commercially available biopharmaceuticals are frozen or freeze-dried in vials. The temperature at which ice nucleates and its distribution across vials in a batch is critical to the design of freezing and freeze-drying processes. Here we study experimentally how the level of particulate impurities - a key parameter in pharmaceutical manufacturing - affects the ice nucleation behavior. Samples prepared under particulate-free conditions were found to nucleate at significantly lower temperatures and with more variability than samples of the same composition that were prepared under standard laboratory conditions, i.e., without using any means of lowering particulate counts. In contrast, spiking solutions with silver iodide particles resulted in significantly higher and less variable nucleation temperatures. These findings confirm that the level of particulates has a relevant effect on the rate of ice nucleation under conditions of industrial relevance. We further assessed the nucleation behavior of two biopharmaceuticals, a vaccine based on a viral vector and a mAb, and observed major differences in their nucleation behavior. This emphasizes the importance of measuring the ice nucleation behavior of biopharmaceuticals during process design.

Plasma-assisted destruction of polystyrene nanoplastics.

This study addresses the critical need for the effective removal of nanoplastics (1 nm to 1000 nm), which pose a significant environmental challenge due to their ease of entry into biological systems and poorly understood health impacts. We report our investigation of a plasma-assisted methodology with a falling film plasma reactor to destroy and remove 200 nm polystyrene nanoplastic particles from their aqueous solution. Using the nanoparticle tracking analysis, size exclusion chromatography, and total organic carbon (TOC) analysis, we examined the degradation kinetics of the nanoplastics upon plasma-assisted treatment. A nanoplastic removal rate of 98.4% by particle count was achieved in one hour of treatment. This rate increased to 99.3% after three hours of treatment, along with a 27.4% reduction in the TOC of the solution. The chromatography results indicate that the observed elimination of nanoplastic contaminants was likely through the production of short polystyrene oligomers with molecular weights roughly equivalent to those of two styrene units. The superior efficacy of the plasma-assisted methodology over traditional ozonation to destroy nanoplastics was also illustrated. Our results not only elucidate a hypothesized polystyrene radical decay mechanism but also demonstrate a potential and complementary approach for mitigating nanoplastic pollution in water purification strategies.

Respiratory extracellular vesicle isolation optimization through proteomic profiling of equine samples and identification of candidates for cell-of-origin studies.

Growing evidence supports the importance of extracellular vesicle (EV) as mediators of communication in pathological processes, including those underlying respiratory disease. However, establishing methods for isolating and characterizing EVs remains challenging, particularly for respiratory samples. This study set out to address this challenge by comparing different EV isolation methods and evaluating their impacts on EV yield, markers of purity, and proteomic signatures, utilizing equine/horse bronchoalveolar lavage samples. Horses can serve as effective translational animal models for respiratory studies due to similarities with human immune responses, shared environmental exposures, and naturally occurring respiratory diseases including asthma. Further, horses are long-lived large animals that allow for longitudinal sample collection, and provide large sample volume and cell yield, which are particularly useful since EV research is commonly limited by low sample yields. Here, EVs were isolated from horse bronchoalveolar lavage fluid (BALF) using four different methods (ultracentrifugation, microcentrifugation, and two sizes of size exclusion chromatography columns) and characterized by measuring particle counts, EV purity, total protein yield, and proteomic cargo, with a specific focus on vesicle surface marker expression potentially informing cell type of origin. We found that size exclusion chromatography yielded the highest particle counts, greatest EV purity markers and elevated vesicle surface marker expression. Overall proteomic profiles differed across isolation methods, with size exclusion chromatography clustering separately from centrifugation. Taken together, our results demonstrate that different isolation methods impact characteristics of EVs, notably that size exclusion chromatography, compared to centrifugation methods, resulted in higher EV purity and better characterized proteomic diversity, including information on EV cell-of-origin. This is the first study to characterize proteomic profiles of EVs following different isolation methods using equine BALF. The results of this study will pave the way for future studies using equine and human samples to characterize respiratory tract EVs.

Tears as a repository for particulate matter PM 1.0, 2.5 and 10 in an urban environment

Aims/Purpose: This study investigates the potential of tear fluid analysis as a non‐invasive method to monitor air pollution impact on an exposed body tissue, represented by the ocular surface [1,2]. In particular, we characterized the particulate matter (PM) in tears in healthy volunteers exposed or not to an urban environment.Methods: Twenty healthy volunteers were enrolled from personnel staff, ten were exposed to urban traffic in Bologna, Italy in the period January‐April 2024 for a minimum of 2 hours, and ten were not. A minimum of 5 μL tear were sampled from the lower conjunctival sac, deposited onto glass slides or polycarbonate filters, allowed to dry and stored at room temperature in a sterile Petri dishes, until observation. Scanning electron microscopy (SEM, Zeiss) was employed to analyze and characterize the PM present in the samples. Particles were categorized by size, morphology, and elemental composition using energy‐dispersive X‐ray spectroscopy (EDS). PM analysis and characterization in tears was compared to filters obtained for gravimetric analysis of airborne PM collected via filtration in Milan.Results: SEM analysis revealed predominantly fine particles (PM2.5), with occasional larger ones (PM10). Elemental analysis identified common PM pollutants such as carbon, oxygen, sulfur, nitrogen, and trace metals like iron and calcium. The particle count per unit area (15 eV, 400x) showed a range of densities across different samples, with a difference in PM levels between exposed and non exposed subjects.Conclusions: The study demonstrated that SEM analysis of tear samples is a viable method for detecting PM levels in tears, and a notable difference between exposed and non exposed subjects. This highlights the potential role of tear analysis in monitoring environmental pollution. This non‐invasive approach could be pivotal in understanding the impact of air pollution on the ocular surface.References M.A. Gutiérrez, D Giuliani, A.A. Porta, D. Andrinolo D, J Ophthalmic Vis Res 2019, 14(4), 419‐427. O. Girshevitz, N. Cohen‐Sinai, A. Zahavi, Y. Vardizer, D. Fixler, N. Goldenberg‐Cohen, J. Pers. Med. 2022, 12, 1633.

Pneumatic tube transport of trastuzumab in IV bags-Effect of headspace and surfactant on subvisible particle formation.

In hospitals, IV bags can be prepared in advance for logistical and microbial safety reasons in a compounding unit and then transported to wards. Transport of protein drugs using a pneumatic tube system has been reported to result in high particle levels. In this study, pneumatic tube transport of trastuzumab in saline polyolefin bags was compared to delivery by hospital porters using an electric platform truck in an underground tunnel system. The transport was tracked using designed smart labels. Two strategies to prevent particle formation, removing headspace and adding the surfactant polysorbate 20 were evaluated. The transport by pneumatic tube had a higher level of shock and vibration than truck delivery. The total particle count measured using flow microscopy also increased more for pneumatic transport than for transport by vehicle. Removing the headspace decreased particle formation for both transports. Surfactant decreases particles over 10 µm for trastuzumab in saline IV bags but increases the total particle levels. Pneumatic tube transport of saline in polyolefin bags resulted in high particle levels and surfactant increased the total particle count. Removing headspace is a measure that can be incorporated into compounding practices to cover for inadequate surfactant levels in IV bags.

Simulation for the Calibration of Radiation Housekeeping Monitor Onboard BepiColombo/MMO and Application to the Inner Heliosphere Exploration

AbstractAlthough primarily a housekeeping instrument for measuring ambient radiation, the Solar Particle Monitor (SPM) onboard BepiColombo can measure high‐energy particles, making it useful for observing phenomena such as galactic cosmic rays and Solar Energetic Particles (SEPs). However, it only records time‐series data of particle energy loss and counts, which requires characterization by radiation simulation for scientific analysis. In this study, a physical model of the SPM was constructed using the “Geant4” radiation simulation toolkit to investigate its response to charged particles. The probability density functions were derived from the response functions to indicate the proportion of particles in each energy range among the SPM counts. Finally, we inverse‐calculated the flux from the counts in the corresponding energy ranges. We applied this method to data from the terrestrial radiation belt and SEPs in March 2022. The results agreed with the empirical radiation belt model and another instrument onboard BepiColombo, demonstrating the validity of the method. This study highlights the potential for scientific applications of housekeeping instruments and suggests the broader use of similar methods on other missions for expanding inner heliosphere multi‐point exploration.