Medial arterial calcification is a common lesion associated with aging, chronic kidney disease, and diabetes that can lead to poor outcomes. Because the calcification is extensive when first apparent clinically or even radiologically, optimal therapy should target reversal in addition to prevention. However, studies to date suggest that medial calcification is irreversible under physiological conditions. This lack of reversal was investigated further by implanting calcified human arteries or hydroxyapatite subcutaneously into mice, or culturing them with murine osteoclasts in vitro. Calcified human tibial arteries, obtained from amputations and previously frozen, were implanted subcutaneously in the dorsum of mice. Mineral content was measured by microcomputed tomography before and after implantation and compared with the calcium content of implanted pure hydroxyapatite or murine bone particles, along with histology. Calcified arteries were also incubated in vitro with osteoclasts generated by treating murine macrophages with receptor activator of NF-κB (nuclear factor kappa B). There was no decrease in mineral content of implanted arteries over 6 weeks and only minimal loss of calcium in devitalized bone particles, compared with almost complete resorption of hydroxyapatite. No resorption of hydroxyapatite occurred when implanted within a cell-impermeable diffusion chamber. Multinucleated giant cells, negative for osteoclast markers, were numerous among implanted hydroxyapatite, but rare in implanted arteries and bone. There was no histological evidence of resorption in calcified arteries incubated with osteoclasts. Hydroxyapatite is readily reabsorbed in vivo by a cell-mediated process not involving osteoclasts. The lack of resorption of medial arterial calcifications, even in the presence of osteoclasts, indicates that calcifications have properties that prevent cell-mediated resorption. Further studies are needed to identify these properties and develop strategies to overcome this.

The purpose of the research is to experimentally investigation of physical processes in the interelectrode space of the needle-air-liquid-plane system in a strong non-uniform electric field with a positive tip. Methods. Video images of the development of a corona discharge and a microplasma structure are analyzed; I-V characteristics are measured, synchronized with the video image. Results. An external method for obtaining a stable cold circuit flow in a needle-plate electrode system coated with a layer of weakly conductive liquid is used. Current-voltage characteristics are measured in a corona discharge environment. Visual analysis of the CR and MPS glow allows one to evaluate the ionic composition of the CR and MPS. CVCs are measured at the initial stage of MPS development. The mechanism of MPS formation is studied. Conclusion. The study demonstrated that the IVLP system enables a new method for producing stable ion-flux-discharge with a positive tip. The IFD is shown to be consumed only with a positive tip. It was found that IR ignition in this configuration occurs at E* ≈ 3.6 kV/cm and a gradual, smooth increase in current, as the tip-air-flux-discharge system exhibits fluctuations due to unstable ion cloud states. A comparative analysis of the tip field strengths demonstrated that the latest IR ignition parameters are comparable at different polar states, but their ignition mechanisms differ. Visual analysis of the IR and IFD glow spectra allows one to evaluate the ionic composition of the IR and IFD: in the IVLP system, the contribution of OH and O 2 + is noticeable, which differs from the IAF system, where N 2 and N 2 + emission predominate. The generation of a micro-electron-like particle in the IVZhP system occurs without preliminary ignition of a static CR, as the CR immediately develops into a micro-electron-like particle. The obtained results reveal the potential of this method for the controlled generation of CP and expand our understanding of the principle of ionization with a positive tip.

Optimizing Particle Visualization in the Classroom: Design, Construction, and Evaluation of Cloud Chambers and Their Use with a Cathode Ray Tube

Rapid visual authentication of high-temperature Daqu Baijiu using porphyrin signal amplification and smartphone-based cloud machine learning.

Efficient hydrogen purification from methanol steam reforming (MSR) faces challenges due to H2/CO2 kinetic diameter overlap and energy-intensive traditional methods. Here, we report a biomimetic hourglass-shaped covalent organic framework (COF) membrane via sequential spray coating of opposite charged COF nanosheets, mimicking aquaporin-like hierarchical channels. The sandwich structure (large-pore sulfonated COF outer layers, narrow-pore guanidinium COF middle layer) enables dual-functionality: outer TpBD-SO3H layers perform as the diffusion chamber (2.5nm pores) and protective layer, whereas the middle TpTGCl layer (0.8nm pores) traps CO2 via strong electrostatic interactions. The membrane achieves a H2 permeance of 2833 GPU and H2/CO2 selectivity of 21, surpassing the 2008 Robeson upper bound. Spray coating enables scalable fabrication of 5000 cm2 defect-free membranes on porous substrate with high mechanical stability and chemical resistance (mass loss<0.3% in 150°C methanol). Separation process simulations show a two-stage system boosts H2 purity to 96.7% with 94.3% recovery, outperforming pressure swing adsorption (PSA) in efficiency and energy consumption. This modular design offers a sustainable, scalable solution for industrial hydrogen purification and gas separation.

Abstract Efficient hydrogen purification from methanol steam reforming (MSR) faces challenges due to H 2 /CO 2 kinetic diameter overlap and energy‐intensive traditional methods. Here, we report a biomimetic hourglass‐shaped covalent organic framework (COF) membrane via sequential spray coating of opposite charged COF nanosheets, mimicking aquaporin‐like hierarchical channels. The sandwich structure (large‐pore sulfonated COF outer layers, narrow‐pore guanidinium COF middle layer) enables dual‐functionality: outer TpBD‐SO 3 H layers perform as the diffusion chamber (2.5 nm pores) and protective layer, whereas the middle TpTGCl layer (0.8 nm pores) traps CO 2 via strong electrostatic interactions. The membrane achieves a H 2 permeance of 2833 GPU and H 2 /CO 2 selectivity of 21, surpassing the 2008 Robeson upper bound. Spray coating enables scalable fabrication of 5000 cm 2 defect‐free membranes on porous substrate with high mechanical stability and chemical resistance (mass loss &lt; 0.3% in 150 °C methanol). Separation process simulations show a two‐stage system boosts H 2 purity to 96.7% with 94.3% recovery, outperforming pressure swing adsorption (PSA) in efficiency and energy consumption. This modular design offers a sustainable, scalable solution for industrial hydrogen purification and gas separation.

The adoption of the Internet of Things (IoT) for the application of smart health is an effective method for distributed and intelligent automated diagnosis systems. Fetal movement is a basic index of fetal well being. IoT based fetal health classification leverages IoT technology to remotely assess and monitor fetal well being in real time. Continuous data streams including uterine contractions, fetal heart rate (FHR), and movement patterns can be gathered and analyzed by incorporating sensors with cloud machine learning (ML) and computing algorithms. This allows prompt diagnosis of distress indicators or abnormalities, simplifying quick measures to optimize prenatal care outcomes. Furthermore, IoT based systems provide an opportunity for personalized monitoring of individual pregnancies, enhancing fetal and maternal health monitoring through gestation. On the other hand, the present technology in medical applications could not offer an easily accessible, long term, and effective way for fetal movement monitoring. Lately, ML and deep learning (DL) approaches have been considered appropriate for the automatic classification of fetal health. This study presents an IoT assisted Fetal Health Detection and Classification using the Mother Optimization Algorithm with Deep Learning (AFHDC MOADL) method. The goal of the AFHDC MOADL technique is to accurately classify fetal health into three different classes such as normal, suspect, and pathological. In the AFHDC MOADL technique, a multi faceted process is involved. Primarily, the AFHDC MOADL technique involves IoT devices for the data acquisition process which collects fetal health related data. Besides, the AFHDC MOADL technique undergoes data pre processing in two ways such as K nearest neighbor (KNN) based data imputation and standard scaler. The AFHDC MOADL technique designs a mother optimization algorithm (MOA) to decrease the high dimensionality problem, which selects an optimal subset of features. A graph convolutional neural network (GCN) model is exploited for the fetal health classification. Finally, the root mean square propagation (RMSProp) optimizer can be utilized for optimum hyper parameter selection of the GCN technique. The simulation outcomes of the AFHDC MOADL algorithm can be assessed on the Fetal Health Classification dataset from the Kaggle dataset. The experimental validation highlighted the significant performance of the AFHDC MOADL technique over recent DL approaches.

Abstract A large convection cloud chamber has been proposed for exploring aerosol–cloud–drizzle interactions under well‐controlled turbulent conditions. Recent theoretical and numerical studies suggest that a convection cloud chamber with two heated and two cooled sidewalls can significantly enhance the liquid water content and thus benefit drizzle initiation. However, a chamber with such a sidewall configuration develops stable stratification and extremely weak turbulence therein. In this study, we conduct large‐eddy simulations of a tall convection chamber with five different sidewall configurations consisting of alternating warm and cold patches. For each configuration, the total surface area of warm patches equals that of cold patches, resulting in the same expected cloud‐free supersaturation based on a flux budget model. Results show that changing the sidewall configuration, while keeping all other factors constant, can substantially enhance turbulent mixing and improve the uniformity of thermodynamic and cloud microphysical properties in the bulk region of the chamber. In addition, turbulence strength is positively correlated with liquid water content and negatively correlated with cloud droplet number concentration, consistent with theoretical predictions. Our results highlight the advantage of building a large cloud chamber using modular patches with individually controllable temperature and humidity to achieve well‐mixed conditions.

Soil bacteria are a major source of clinically useful antibiotics, yet the majority of soil-dwelling micro-organisms remain uncultivable by standard laboratory methods. To access this untapped microbial diversity, we employed microbial diffusion chambers to isolate bacteria from ten Australian soil samples. A total of 1,218 bacterial isolates were recovered, representing a diverse collection spanning 61 genera from 32 families, covering the major known phyla of soil bacteria. Antibiotic activity screening revealed that 16% of isolates inhibited the growth of at least 1 of Escherichia coli or Staphylococcus aureus, with 120 isolates displaying activity against multidrug-resistant pathogens including methicillin-resistant S. aureus and vancomycin-resistant Enterococcus faecium. Mass spectrometry-based dereplication using GNPS identified known antibiotics in 33% of bioactive strains, including actinomycin D, nonactins and valinomycin. Genomic analysis confirmed the presence of corresponding biosynthetic gene clusters, while targeted analysis of selected strains uncovered production of additional antibiotics such as nigericin and streptothricin that were not initially detected by MS. Our results demonstrate that diffusion chambers enhance bacterial recovery from soil and show the benefits of a combined pipeline including bioactivity screening, MS and genomics for effective antibiotic dereplication and discovery.

Abstract. Aerosol particles play a critical role as cloud condensation nuclei (CCN) in the atmosphere. The capacity of aerosol particles to activate into cloud droplets is measured experimentally using CCN counters (CCNCs). Recent findings suggest that the co-condensation effect of semi-volatiles can enhance aerosol particle growth and cloud droplet activation. Conventional CCNCs, such as the streamwise CCNC, heat particles as they transit the CCNC column and may inadvertently not capture the co-condensation effect, leading to an underestimate in CCN concentrations. Additionally, streamwise CCNCs struggle to achieve supersaturations below 0.13 %, limiting their applicability for studying hydrophilic particles like (NH4)2SO4 larger than 111 nm. To address these limitations, we developed the Horizontal Cloud Condensation Nuclei Counter (HCCNC), which can generate supersaturation (SS) down to 0.05 % for temperatures down to 4 °C. This study presents the development of the HCCNC, providing a detailed technical description of its 3D geometry, computational fluid dynamics simulations and the key components that demonstrate its performance, showing accurate performance at low temperatures and SS, which the widely used, commercially available Droplet Measurement Technologies Inc. (DMT) CCNC cannot achieve. The main chamber parts were 3D-printed from an aluminium alloy. Sampling and humidity generation followed the principle of the previously used continuous-flow thermal-gradient diffusion chambers. Particles were detected using a commercially available optical particle counter (OPC; MetOne Instruments, Inc., Model 804). The instrument's performance is validated by conducting laboratory tests using ammonium sulfate ((NH4)2SO4) particles in the size range between 50 and 200 nm and for temperatures between 30 and 8 °C. Future work will focus on exploring the co-condensation effect on cloud droplet activation of levoglucosan and ammonium sulfate particles.

A preliminary design of cloud chamber for enhancing interconnections between cosmic rays and humans

Abstract The mechanisms controlling ice crystal growth rates at low temperature (T &lt; −40°C) are relatively unknown. A new thermal gradient diffusion chamber was developed to capture high-resolution images of ice crystals growing from a substrate with minimal vapor competition or shadowing. Time series of dimensional growth rates of columnar ice crystals at cirrus-like temperatures (from −67° to −46°C) and moderate to high supersaturation (28%–80%) were determined from these images. The results show that growth rates of both primary facet dimensions (a and c) decrease over about the first hour of each experiment but asymptotically approach constant values. The a-dimensional growth rate is well correlated with the environmental conditions, declining with decreasing temperature and increasing supersaturation. In contrast, c-dimensional growth rates from individual experiments are not correlated with temperature and slightly correlated with supersaturation. Together, these trends produce aspect ratios that approach constant values that are negatively correlated with temperature. The ratio of the asymptotic growth rates (dc/da) is tightly correlated with the aspect ratio (ϕ = c/a), which supports the predictions of crystal growth theory assuming that steps nucleate near facet edges. In contrast, predictions from capacitance theory are not consistent with the measurements.

Isoprene (C5H8) is the non-methane hydrocarbon with the highest emissions to the atmosphere. It is mainly produced by vegetation, especially broad-leaved trees, and efficiently transported to the upper troposphere in deep convective clouds, where it is mixed with lightning NOx. Isoprene oxidation products drive rapid formation and growth of new particles in the tropical upper troposphere. However, isoprene oxidation pathways at low temperatures are not well understood. Here, in experiments at the CERN CLOUD chamber at 223 K and 243 K, we find that isoprene oxygenated organic molecules (IP-OOM) all involve two successive {{{rm{OH}}}}^{bullet} oxidations. However, depending on the ambient concentrations of the termination radicals ({{{{rm{HO}}}}_{2}}^{bullet},,{{{rm{NO}}}}^{bullet}, and {{{rm{NO}}}}_{2}^{bullet}), vastly-different IP-OOM emerge, comprising compounds with zero, one or two nitrogen atoms. Our findings indicate high IP-OOM production rates for the tropical upper troposphere, mainly resulting in nitrate IP-OOM but with an increasing non-nitrate fraction around midday, in close agreement with aircraft observations.

Isoprene oxygenated organic molecules (IP-OOM) can nucleate new particles in the upper troposphere. These particles may grow into cloud condensation nuclei and influence the clouds and climate. However, little is known about the individual species driving growth and whether they undergo condensed-phase reactions. We conducted isoprene oxidation experiments at 223 and 243 K in the CLOUD chamber at CERN. Gas-phase concentrations were measured with chemical ionization mass spectrometers (NO3–-CIMS, Br–-MION2-CIMS, and NH4+-CIMS). Growth rates from 8 to 20 nm were measured by a Neutral Cluster and Air Ion Spectrometer. Particle-phase composition was measured by a filter sampling chemical ionization mass spectrometer. We use the diagonal volatility basis set (dVBS) analysis framework to compare gas- and particle-phase measurements and assess species and processes influencing growth. We find that kinetically limited condensation of a few species dominates particle composition and growth. Particle-phase processes, including oligomerization and organonitrate hydrolysis, do not influence the early growth. dVBS growth rate predictions can explain 90% of the measured growth, dominated by kinetic condensation of low-volatility species. Our findings indicate that initial growth of IP-OOM particles under cold, low-acid conditions may be controlled and modeled by the kinetically limited condensation of low-volatility compounds.

miRNAs regulate cancer progression and serve as both biomarkers and therapeutic targets in chemotherapy and gene therapy. Current analytical platforms lack the capacity to concurrently satisfy single-cell resolution and target specificity while maintaining high-throughput performance and cost-effectiveness. This limitation underscores the critical demand for innovative precision detection technologies. In this study, we focused on two key regulatory miRNAs in breast cancer therapeutic assessment and developed a "space-for-time" strategy using dual-isotope ICP-MS for single-cell miRNAs quantification. The spatial expansion of analytes via single hydrogel microbead encapsulation and collision gas utilization significantly prolonged single-particle ion cloud duration, overcoming the limitations of traditional quadrupole mass spectrometry in the precise dual-isotope quantification. A custom-designed microfluidic chip integrating droplet generation and inertial focusing achieved a single-cell encapsulation efficiency of 57%, thereby enabling a high throughput of ∼1000 cells/min in ICP-MS. In-bead rolling circle amplification combined with nanoprobe labeling enabled femtomolar-level sensitivity for miR-21 and miR-10b detection. This platform facilitated high-throughput, quantitative profiling of miRNA expression across various breast cancer subtypes and offered enhanced resolution of therapeutic responses. In chemotherapy monitoring, our approach revealed early molecular signatures of apoptosis/invasion, outperforming traditional viability and invasion assays in sensitivity and timeliness. For gene therapy evaluation, the platform uncovered subtype-specific differences in miRNA inhibition at single-cell resolution, highlighting tumor heterogeneity thus may potentially guiding precision treatment strategies. Overall, our platform represents a powerful tool for miRNA quantification and therapeutic evaluation, offering robust support for personalized oncology and preclinical drug screening.

Abstract Clouds play a crucial role in Earth’s atmospheric system, influencing weather, climate, and the global water cycle. To better understand fundamental but complex cloud processes, specialized facilities such as cloud chambers are essential for conducting detailed research. In response to this need, the Korea Cloud Physics Experimental Chamber (K-CPEC) was recently constructed. The K-CPEC is a comprehensive facility that incorporates a cloud chamber, an aerosol chamber, a wind tunnel, and various subsidiary systems. This enables a wide range of experiments, such as the generation of diverse aerosols—including those from flare combustion—and their application in cloud formation studies. At its core lies a state-of-the-art cloud chamber, a double-structured, expansion-type chamber with adjustable wall temperature. It features an inner chamber with a volume of approximately 22 m3. The pressure of the inner chamber can be precisely controlled between 30 and 1013 hPa, while its temperature can range from −70° to +60°C. These capabilities allow for the replication and investigation of a variety of cloud types and atmospheric conditions. Extensive preliminary experiments have demonstrated that K-CPEC effectively simulates known atmospheric phenomena such as cloud droplet activation and homogeneous/heterogeneous freezing. Its versatility makes it well suited for various research fields, including cloud microphysics, weather modification, and atmospheric environmental studies. Supported by continued investment from the Korea Meteorological Administration, K-CPEC is poised for fundamental and more refined experimental studies. K-CPEC invites collaboration and participation from the international cloud physics community, recognizing that progress in cloud physics research requires collective efforts from researchers worldwide.

Exploring the impact of surface topography on Rayleigh-Bénard dry convection in the Pi cloud chamber using OpenFOAM: In cylindrical and rectangular geometries

Abstract. In this study, we analyzed the particle characteristics and cloud droplet growth properties of NaCl and CaCl2, which are powder-type hygroscopic materials applied in cloud seeding experiments, using the Korea Cloud Physics Experimental Chamber (K-CPEC) facility at the Korea Meteorological Administration/National Institute of Meteorological Sciences (KMA/NIMS) in South Korea. The aerosol chamber (volume 28.3 m3) enabled the observation of particle characteristics in an extremely dry environment (relative humidity (RH) &lt; 1 %) that was clean enough to ignore the influence of background aerosols. The cloud chamber featured a double-structure design, with an outer (130 m3) and inner (22.4 m3) chamber. The inner chamber allowed the precise control of air pressure (1013.25–30 hPa) and wall temperature (−70–60 °C), facilitating cloud droplet growth through quasi-adiabatic expansion. In this study, a cloud chamber experiment was conducted to simulate both wet adiabatic and stable environmental lapse rate conditions. The experiments were initiated at low RH (&lt; 60 %), and the variations in the cloud droplet concentration and diameter were observed as RH increased, leading to supersaturation (RH &gt; 100 %) and subsequent cloud droplet formation. NaCl and CaCl2 powders showed distinct particle growth behaviors owing to the differences in their deliquescence and hygroscopicity. The rate of cloud droplet formation in the NaCl powder experiments was slower than that for CaCl2; however, the mean and maximum droplet diameters were approximately 2–3 and 10–20 µm larger, respectively. The particle diameter, including aerosols and droplets, varied from 1 to 90 µm, and large cloud droplets (30–50 µm) that served as the basis for drizzle embryo formation were also observed. Our study provides valuable insights for the development of new seeding materials and advanced cloud seeding experiments.

Ecosystems harbor millions of environmental microbes, some of them capable of producing biotechnologically relevant products such as enzymes, vitamins, amino acids, organic acids, anti-parasitic agents, and antimicrobial agents. Most of these environmental bacteria are deemed "unculturable" as the laboratory culturing methods fail to meet their nutritional/environmental requirement. Moreover, as they coexist in nature, they may also be dependent on a nutrient/metabolite produced by another member of the microbial community. Bringing the "uncultured" microbial diversity into the culture will present an opportunity to explore the vast array of bioactive products they may encode. This article describes the implementation of the iChip technology, a multichannel diffusion chamber developed for a high-throughput, in situ culturing of the "unculturable" bacteria. Given the global menace of antimicrobial resistance, the article provides a detailed protocol for in situ cultivation and recovery of isolates from the microbial 'dark matter' capable of producing antimicrobial agents, as an example. This protocol describes the steps involved, right from the soil sample collection step to the recovery of isolates, and highlights the plausible factors that may influence the success of isolation. The use of this technology not only facilitates the isolation of otherwise "unculturable" bacteria for antibiotic discovery but also enables researchers to delve into the complex soil ecology, which can then be tapped into for a myriad of other applications.

Measurement of radon concentration in laboratories of the civil engineering course of Federal Technological University of Parana and the contribution of construction materials to dose limits.