Droplet Count Research Articles

Gestational Diabetes-like Fuels Impair Mitochondrial Function and Long-Chain Fatty Acid Uptake in Human Trophoblasts.

In the parent, gestational diabetes mellitus (GDM) causes both hyperglycemia and hyperlipidemia. Despite excess lipid availability, infants exposed to GDM are at risk for essential long-chain polyunsaturated fatty acid (LCPUFA) deficiency. Isotope studies have confirmed less LCPUFA transfer from the parent to the fetus, but how diabetic fuels impact placental fatty acid (FA) uptake and lipid droplet partitioning is not well-understood. We evaluated the effects of high glucose conditions, high lipid conditions, and their combination on trophoblast growth, viability, mitochondrial bioenergetics, BODIPY-labeled fatty acid (FA) uptake, and lipid droplet dynamics. The addition of four carbons or one double bond to FA acyl chains dramatically affected the uptake in both BeWo and primary isolated cytotrophoblasts (CTBs). The uptake was further impacted by media exposure. The combination-exposed trophoblasts had more mitochondrial protein (p = 0.01), but impaired maximal and spare respiratory capacities (p < 0.001 and p < 0.0001), as well as lower viability (p = 0.004), due to apoptosis. The combination-exposed trophoblasts had unimpaired uptake of BODIPY C12 but had significantly less whole-cell and lipid droplet uptake of BODIPY C16, with an altered lipid droplet count, area, and subcellular localization, whereas these differences were not seen with individual high glucose or lipid exposure. These findings bring us closer to understanding how GDM perturbs active FA transport to increase the risk of adverse outcomes from placental and neonatal lipid accumulation alongside LCPUFA deficiency.

Lab-In-Fiber Optofluidic Device for Droplet Digital Polymerase Chain Reaction (DdPCR) with Real-Time Monitoring.

Droplet microfluidic systems have emerged as indispensable and advanced tools in contemporary biological science. A prominent example is the droplet digital polymerase chain reaction (ddPCR), which plays a pivotal role in next-generation sequencing and the detection of rare nucleic acids or mutations. However, existing optical detection configurations are bulky, intricate, and costly, and require meticulous optical alignment to optimize fluorescence sensing. Herein, we propose a lab-in-fiber optofluidic system (LiFO), which provides a stable and compact footprint, self-alignment, and enhanced optical coupling for high-accuracy ddPCR. Moreover, LiFO could expand its capabilities for multiangle-scattering light collection in which we collect focused forward-scattering light (fFSL) to enable real-time droplet counting and size monitoring. To accomplish these attributes, LiFO incorporates optical fibers, along with fabricated PDMS grooves, for a self-aligned optical setup to implement simultaneous fluorescence and scattering detection. Furthermore, LiFO harnesses the concept of flowing droplets functioning as microlenses, which allows us to collect and translate fFSL signals into droplet size information. We have demonstrated the effectiveness of LiFO in ddPCR applications, illustrating its capacity to enhance the accuracy and precision of DNA quantification. Notably, LiFO exhibits improved linearity in the measurement of serial DNA dilutions, reflected by an increase in R2 from 0.956 to 0.997. These results demonstrate the potential of LiFO to serve as a valuable tool across a wide spectrum of droplet microfluidic platforms, offering opportunities for advancement in practical applications.

Effectiveness of a suction device for containment of pathogenic aerosols and droplets.

As the global community begins recovering from the COVID-19 pandemic, the challenges due to its aftermath remain. This health crisis has highlighted challenges associated with airborne pathogens and their capacity for rapid transmission. While many solutions have emerged to tackle this challenge, very few devices exist that are inexpensive, easy to manufacture, and versatile enough for various settings. This paper presents a novel suction device designed to counteract the spread of aerosols and droplets and be cost-effective and adaptable to diverse environments. We also conducted an experimental study to evaluate the device's effectiveness using an artificial cough generator, a particle counter, and a mannequin in an isolated system. We measured droplet removal rates with simulated single and repeated cough incidents. Also, measurements were taken at four distinct areas to compare its effectiveness on direct plume versus indirect particle removal. The device reduced airborne disease transmission risk, as evidenced by its capacity to decrease the half-life of aerosol volume from 23.6 minutes to 15.6 minutes, effectively capturing aerosol-sized droplets known for their extended airborne persistence. The suction device lessened the peak total droplet volume from peak counts. At 22 minutes post peak droplet count, the count had dropped 24% without the suction device and 43% with the suction device. The experiment's findings confirm the suction device's capability to effectively remove droplets from the environment, making it a vital tool in enhancing indoor air quality. Given the sustained performance of the suction device irrespective of single or multiple cough events, this demonstrates its potential utility in reducing the risk of airborne disease transmission. 3D printing for fabrication opens the possibility of a rapid iterative design process, flexibility for different configurations, and rapid global deployment for future pandemics.

Integrated Droplet-Based Digital Loop-Mediated Isothermal Amplification Microfluidic Chip with Droplet Generation, Incubation, and Continuous Fluorescence Detection.

This study integrated sample partition, incubation, and continuous fluorescence detection on a single microfluidic chip for droplet-based digital Loop-Mediated Isothermal Amplification (LAMP) of nucleic acids. This integration eliminated the need to transfer reactions between different platforms, avoiding sample contamination and loss. Prior to the reaction, filling the channels with an oil phase and adding a glass cover slip on top of the chip overcame the problem of bubble generation in the channels during the LAMP reaction due to heating. Additionally, using two fluorescence intensity thresholds enabled simultaneous detection and counting of positive and negative droplets within a single fluorescence detection channel. The chip can partition approximately 6000 droplets from a 5 µL sample within 10 min, with a droplet diameter of around 110 µm and a coefficient of variation (CV) value of 0.82%. Staphylococcus aureus was quantified via the proposed platform. The results demonstrated a highly accurate correlation coefficient (R = 0.9998), and the detection limit reached a concentration of 1.7 × 102 copies/µL. The entire process of the droplet digital LAMP reaction, from droplet generation to incubation to quantitative results, took a maximum of 70 min.

EVALUATING THE SAFETY AND THERAPEUTIC EFFICACY OF INTRAVENOUS HYDROGEN NANOBUBBLE INFUSIONS IN A HYPERCHOLESTEROLEMIC RAT MODEL

Hydrogen has emerged as a promising candidate due to its antioxidant properties and potential to modulate electron flow, enhancing mitochondrial energy metabolism and reducing oxidative stress. In this study, hypercholesterolemia male Wistar rats were utilized to investigate the safety and efficacy of intravenous hydrogen nanobubble solution (HNB). The study assessed serum lipid levels, complete blood count, and organ health following HNB administration compared to positive (simvastatin) and negative controls. Bayesian statistics were used to validate the findings. The administration of HNB did not adversely affect the immediate survival of the rats on a high fat diet (HFD), whereas simvastatin significantly reduced survival rates. It showed a dose dependent immunomodulatory effect, reducing white blood cell, lymphocyte, and monocyte counts. It also influenced erythropoiesis, as indicated by increased red blood cell counts and hemoglobin levels. A significant elevation in platelet counts was observed, suggesting potential effects on platelet production or lifespan. The study also noted changes in liver enzyme levels, with HNB indicating potential hepatoprotective effects. Furthermore, HNB treatment decrease in mean fat droplet count, suggesting a mitigation of diet induced hepatic steatosis. The findings suggest that HNB may serve as a protective agent against the deleterious effects of a high-fat diet, offering immunomodulatory and hepatoprotective benefits. This study provides a foundation for considering HNB as a potential therapeutic intervention for hypercholesterolemia and warrants further investigation into the long-term impacts of nanobubble treatment on diet induced pathologies. The consistency of results across traditional statistical significance and Bayesian evidence strengthens the validity of the observed treatment-specific effects.

Microscopic investigation and local standard deviation analysis of liquid propane jets in supercritical environment

To improve the thermal efficiency of engines, the temperature and pressure in the combustion chamber are continually increased, potentially reaching the critical points of the fuels. Additionally, light fuels such as liquid ammonia and propane are utilized to reduce carbon emissions. The relatively low critical temperature of light fuels facilitates their transition into a supercritical state, which greatly change the jet characteristics. To gain a deeper understanding of the supercritical transition of fuels, jets of liquid propane are investigated through high-speed microscopic imaging technology, covering subcritical to supercritical environmental conditions. Liquid propane is injected through a transparent flat nozzle to observe the internal flow states within the nozzle. For image and data processing, local standard deviation (LSD) analysis and a Residual Network (ResNet-50) model are employed to identify the structures within the mixing region. Droplets counting and frequency domain analysis are also performed to reveal the features of supercritical transition. The findings highlight the importance of mask size in the jet feature extraction. Large mask highlights large scale structures including jet surface and mixing region structures, while small mask brings about full-scale feature including droplets and all other features. A criterion for mixing regime classification based on reduced temperature (Tr) and reduced pressure (Pr) is established directly from image data using the ResNet-50 model, where a condition of Tr1.6Pr0.4 ≥ 1.067 indicates a transcritical mixing regime. Both droplet counting and frequency domain analysis corroborate this mixing regime criterion. These insights enhance our understanding of supercritical transitions and are useful for simulation verifications.

An image segmentation of adhesive droplets based approach to assess the quality of pesticide spray

Pesticide spray is a widely used chemical control method to minimize biological disasters in the agriculture industry. It is important to evaluate the efficacy and the quality of a pesticide sprayer, however, it cannot be conveniently achieved due to the lack of accessibility to the sprayed droplets and the intensity of the associated work. This paper proposes a novel method, based on an image processing-based approach, to assess the spray quality. The proposed method uses a combination of algorithms and criteria functions; such as, the maximum between-cluster variance algorithm, area threshold criteria, roundness factor, mathematical morphology operations, and the optimized watershed algorithm, to segment and assess the dark blue adhesive droplet images on a water-sensitive paper, placed in the crop field. In this work, three kinds of evaluation experiments are considered: (i) the manual analysis via droplet counting and processing, (ii) the automatic analysis by the commercially available droplet analyzer by Shenzhen DJI Co. Ltd., and (iii) the novel image processing based method introduced in this paper. The experimental results show a better consistency between the introduced novel method and the manual method. The former, however, provides a convenient and rapid way to assess the spray quality. It comes with an assessment algorithm along with an embedded device that provides a hardware view of the spray quality.

Estimating droplet size and count distributions over a prolonged period of time following a cough in indoor environments

An empirical correlation and a set of machine learning (ML) models were developed to estimate droplet size and count distributions over an extended duration after a cough at different relative humidities (RHs), air temperatures and locations within an indoor environment. Experiments covered RHs of 20%–80% and air temperatures of 21 °C–26 °C. Droplet count distributions for 4 size bins (0.3–0.5, 0.5–1, 1–3 and 3–5 μm) were recorded for 70 min within the distance of 2 m from the cough source. Different ML models, including decision tree, random forest and artificial neural network, were trained for each size bin to predict the associated count distribution. Amongst these models, random forest showed a slight superiority in performance. The coefficient of determination for the random forest models ranged from 0.912 to 0.989, indicating robust correlations between the features and the response variables. An empirical correlation was established linking the count distribution of 0.3–0.5 μm droplets to time, RH and distance along the cough direction. Both ML models and the correlation accurately predicted the trends and the distributions, providing valuable data for validating computational simulations and informing indoor environment control systems to reduce the risk of virus transmission.

Ultralow-hysteresis quartz crystal microbalance humidity sensor based on electrospinned cellulose acetate/konjac glucomannan network-like film

There are numerous and significant uses for accurate and reliable humidity detection in day-to-day living. In this study, a QCM humidity sensor based on cellulose acetate/konjac glucomannan (CA/KGM) film was constructed. The elemental composition, morphology and nanostructure of the film were characterized using scanning electron microscopy (SEM), water contact angle tester, X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FT-IR). The CA/KGM QCM humidity sensor exhibited excellent stability, selectivity and repeatability with low humidity hysteresis and short response/recovery time (12.3 s/0.1 s). The experimental results show that the introduction of CA in KGM can dramatically improve the mechanical properties and stability of the composite membrane. The humidity sensing mechanism of the sensor was systematically investigated, and water droplet counting test, fingertip moisture detection and human breath detection were performed. The sensor offers a wide range of potential applications.

Tianhuang formula ameliorates non-alcoholic fatty liver diseases in type 2 diabetic mice through CRLS1-ATF3/ChREBP pathway

ObjectiveTianhuang Formula (THF) is a hospital formula summarized by Professor Jiao Guo's 30 years of clinical experience. Some studies have shown that it can alleviate dyslipidemia in the body. The purpose of this study is to confirm whether THF can improve non-alcoholic fatty liver diseases (NAFLD) in type 2 diabetic mice induced by high-fat diet (HFD)/streptomycin (STZ) and to clarify its potential mechanism. MethodsAfter induction of diabetes, mice were administrated with THF (60 ​mg/kg or 120 ​mg/kg) once daily for 10 weeks. Blood glucose (FBG), glucose tolerance, and insulin resistance (IR) were assayed by oral glucose tolerance test (OGTT) and insulin tolerance test (ITT). Blood lipids, alanine transaminase (ALT), and aspartate transaminases (AST) were detected. Serum fasting insulin (INS) and adiponectin (APN) levels were measured using ELISA. Histological changes in liver and pancreatic islets were observed by H&E staining, followed by Oil Red O staining for liver lipid quantification and periodic acid-Schiff (PAS) staining to detect glycogen accumulation. Western blotting detected the levels of fatty cardiolipin synthase 1 (CRLS1), transcription factor activator 3 (ATF3), and carbohydrate-responsive element binding protein (ChREBP) in the liver. The mRNA transcripts of hepatic inflammatory factors, lipogenesis and lipolysis-related genes, and gluconeogenic enzyme-phosphoenolpyruvate carboxykinase (PEPCK), CRLS1, ATF3, and ChREBP mRNA levels were evaluated by RT-qPCR. ResultsTHF restored impaired glucose tolerance and insulin resistance, respectively. There was an improvement in HFD/STZ-induced liver and islet damage, high serum HDL-C and ANP levels, and a significant decrease in FBG, total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), FFA, INS, ALT, and AST, and lipid droplet counts in the T2DM mice treated with THF. CREBBP binding protein ATF3 mediated the insulin resistance signaling pathway, which regulated glucose and lipid metabolism in the liver. THF upregulated CRLS1, and ChREBP downregulated the expression of downstream ATF3 in the liver. RT-qPCR analysis also systemically indicated that THF suppressed the pathway and key regulators related to inflammation, lipid accumulation, and gluconeogenesis. ConclusionOur findings demonstrated that THF ameliorated lipid profile and attenuated liver steatosis in T2DM mice through CRLS1-ATF3/ChREBP pathway activation.

Effect of atomizer and cross-flows on liquid and gelled Jet A-1 fuel injection

The current study aims to experimentally investigate the effect of atomizer and cross-flow velocities on liquid and gelled Jet A-1 fuels. For gelled Jet A-1, Jet A-1 liquid, Thixatrol® ST and rectified xylene are the base fuel, gellant and solvent, respectively. Gelled Jet A-1 is prepared by adding 85% by weight of base fuel along with 7.5% by weight of gellant and solvent, each at optimum processing conditions. Atomization using a simple-plain-orifice atomizer is investigated to understand its effect on Jet A-1 gel fuel break-up without air cross-flow. Based on the investigation from qualitative flow visualization and quantitative analysis of Jet A-1 gel fuel break-up, a modified simple-plain-orifice atomizer called an internally impinging air-blast atomizer is made. Primary atomization using this new atomizer is studied to understand the break-up of liquid and gelled Jet A-1 gel fuels without any air cross-flow. Secondary atomization of liquid and gel fuel is investigated by transversely injecting fuel into different low-speed subsonic air cross-flow environments. Laser sheet Imaging (LSI) technique is used to capture spray images of both fuels. Break-up mechanisms of both liquid and gel fuels were observed, and the results were compared. Information on the cross-flow air mass flow rate effect on the liquid and gel spray is extracted by developing an algorithm in MATLAB using an image processing tool. Relative droplet size distribution of liquid and gel spray revealed their dependence on cross-flow air mass flow rate. Total droplet count of both liquid and gel fuel decreases significantly as the cross-flow Reynolds’ number increases. At higher cross-flow Reynolds’ number, gel droplets in the flow are observed to be more as compared to liquid fuel.

A one-stage deep learning based method for automatic analysis of droplet-based digital PCR images.

Droplet-based dPCR offers many advantages over chip-based dPCR, such as lower processing cost, higher droplet density, higher throughput, while requiring less sample. However, the stochastic nature of droplet locations, uneven illuminations, and unclear droplet boundaries make automatic image analysis challenging. Most methods currently used to count a large amount of microdroplets rely on flow detection. Conventional machine vision algorithms cannot extract all information of the targets from complex backgrounds. Some two-stage methods, which first locate and then classify droplets according to their grayscale values, require high-quality imaging. In this study, we addressed these limitations by improving a one-stage deep learning algorithm named YOLOv5 and applying it to the detection task to realize one-stage detection. We introduced an attention mechanism module to increase the detection rate of small targets and used a new loss function to speed up the training process. Furthermore, we employed a network pruning method to facilitate the deployment of the model on mobile devices while preserving its performance. We validated the model with captured droplet-based dPCR images and found that the improved model accurately identified negative and positive droplets in complex backgrounds with an error rate of 0.65%. This method is characterized by its fast detection speed, high accuracy, and ability to be used on mobile devices or cloud platforms. Overall, the study presents a novel approach for detecting droplets in large-scale microdroplet images and provides a promising solution for accurate and efficient droplet counting in droplet-based dPCR.

Comparison of breath-guards and face-masks on droplet spread in eye clinics

IntroductionCOVID-19 has impacted ophthalmic care delivery, with many units closed and several ophthalmologists catching COVID-19. Understanding droplet spread in clinical and training settings is paramount in maintaining productivity, while keeping patients and practitioners safe.ObjectivesWe aimed to assess the effectiveness of a breath-guard and a face mask in reducing droplet spread within an eye clinic.MethodsWe performed a randomised trial of droplet spread using a fluorescein-based cough model to assess the efficacy of a ‘breath-guard’ and ‘face-mask’ to prevent the spread of droplets. The ‘cough’ spray was collected on calibrated paper targets. The sheets were photographed under blue light, with an orange filter on the camera; the position and size of the spots was measured with software originally developed for astronomy.We performed 44 randomised coughs; 22 controls with no breath-guard or face-mask, 11 using breath-guard only and 11 with combined breath-guard and face-mask. We compared both the number of droplets detected and the area of drops on paper targets.ResultsThe average number of droplets in the controls was 19,430 (SE 2691), the breath-guard group 80 (SE 19) droplets (P < 0.001); in the combined In the group the count was 5 (SE 2), a significant drop from shield only (P = 0.008). The mean areas of each target covered by spots for each group were 5.7 ± 0.857% (95% CI), 0.004 ± 0.000104% (95% CI) and 0.001 ± 0.0000627% (95% CI) respectively.ConclusionThese results show that the breath-guard alone reduced the droplet count by 99.93%. Combining the breath-guard with a face-mask reduced the droplet count by over 99.98%. Breath-guards are widely used in clinics and this trial demonstrates that breath-guards with face-masks effectively block droplet spray.

Evaluation of expelled droplets through traditional Islamic face coverings.

Expelled droplet count is an important factor when investigating the efficacy of face coverings since higher droplet counts indicate an increased possibility of disease transmission for airborne viruses such as COVID-19. While there is some published work relating facemask style to expelled droplet count during speech, there is no published data regarding the effectiveness of traditional Islamic face coverings such as the ghutra and niqab commonly worn by men and women in the Arabian Peninsula. Measure the effectiveness of worn traditional Islamic face coverings in reducing expelled droplet count during speech. Experimental study SETTING: Biomedical engineering department at a university in Saudi Arabia. Using a previously described low-cost method for quantifying expelled droplets, this study compares droplet counts through commonly worn traditional Islamic face coverings and conventional three-ply surgical masks worn during speech. The device records scattered light from droplets (>5 μm diameter) as they pass through a laser light sheet (520 nm), and then video processing yields droplet counts. Percent reduction in the number of expelled droplets passing through face coverings during speech compared to no face covering MAIN OUTCOME MEASURES: 9-15 recorded samples per face covering (n=3) plus no face covering control (n=1) in three females. The average percent reduction for each mask type compared to no mask trial was 76% for the cotton ghutra, 93% for the niqab, and 95% for the surgical mask. The niqab and ghutra had relatively high variability in droplet reduction. Traditional Islamic face coverings block some expelled droplets, but at lower rates than surgical masks. High standard deviations within facemask groups with high variability in fit (i.e., the cotton ghutra) further denote the importance of fit in face covering effectiveness. Some protection from airborne viruses is likely with traditional Islamic face coverings compared to no mask, but the amount of protection depends on the fit of the face covering. Detectable droplets limited to particles greater than 5 μm diameter with forward expulsion direction. None.

DropTrack—Automatic droplet tracking with YOLOv5 and DeepSORT for microfluidic applications

Deep neural networks are rapidly emerging as data analysis tools, often outperforming the conventional techniques used in complex microfluidic systems. One fundamental analysis frequently desired in microfluidic experiments is counting and tracking the droplets. Specifically, droplet tracking in dense emulsions is challenging due to inherently small droplets moving in tightly packed configurations. Sometimes, the individual droplets in these dense clusters are hard to resolve, even for a human observer. Here, two deep learning-based cutting-edge algorithms for object detection [you only look once (YOLO)] and object tracking (DeepSORT) are combined into a single image analysis tool, DropTrack, to track droplets in the microfluidic experiments. DropTrack analyzes input microfluidic experimental videos, extracts droplets' trajectories, and infers other observables of interest, such as droplet numbers. Training an object detector network for droplet recognition with manually annotated images is a labor-intensive task and a persistent bottleneck. In this work, this problem is partly resolved by training many object detector networks (YOLOv5) with several hybrid datasets containing real and synthetic images. We present an analysis of a double emulsion experiment as a case study to measure DropTrack's performance. For our test case, the YOLO network trained by combining 40% real images and 60% synthetic images yields the best accuracy in droplet detection and droplet counting in real experimental videos. Also, this strategy reduces labor-intensive image annotation work by 60%. DropTrack's performance is measured in terms of mean average precision of droplet detection, mean squared error in counting the droplets, and image analysis speed for inferring droplets' trajectories. The fastest configuration of DropTrack can detect and track the droplets at approximately 30 frames per second, well within the standards for a real-time image analysis.

Effect of Non-Condensable gas on condensing performance of HFE7100 With/Without hydrophobic coating

• Condensing performance of dielectric fluid HFE7100 on heat sink with NCG is studied. • Presence of NCG significantly reduces the condensation heat transfer coefficient. • Hydrophobic coating enhanced the heat transfer coefficient by 15.6 to 31.8% • Heat transfer coefficient is reduced by 60–70% with NCG in the absence of coating. • The coating increased droplet count and detaching rate in the presence of NCG. Dielectric fluids are employed to avoid electric hazards in the immersion cooling. However, non-condensable gases (NCG) may prevail in the system and impair the condenser performance appreciably. The current study focuses on the experimental investigation of condensation with NCG for immersion cooling. This is the first experimental study in the immersion cooling application to examine the condenser performance in the presence and absence of NCG using dielectric fluid. A test rig was designed with vertical fins in a sealed insulated chamber using HFE 7100 dielectric fluid. Experiments were performed in the presence and absence of NCG (0%, 1.2%); with and without hydrophobic coating for variation input heating load (110–400 W) and operating pressures (0.7 atm, 1 atm). It was found that in the absence of coating, the average heat transfer coefficient (AHTC) is reduced by about 60 to 70% after adding NCG and the AHTC increased by about 15.6 to 31.8% after applying the coating. The inherent resistance of the coating layer showed a slight reduction in the AHTC in the absence of NCG. The coating used in this study has improved the condensation efficiency by increasing the droplet count and droplet rate in the presence of NCG. The flow visualization indicates that the droplet detaching from the heat sink is smaller with a higher falling frequency when the coating is imposed.

A New Control Strategy for High-Pressure Homogenization to Improve the Safety of Injectable Lipid Emulsions.

Intravenous lipid emulsions are biocompatible formulations used as clinical nutrition products and lipid-based delivery systems for sparingly soluble drugs. However, the particle-size distribution is associated with risks of embolism. Accordingly, the mean particle diameter (MPD) and particle-distribution tailing (characterized as the pFAT5 value) are critical quality attributes that ensure patient safety. Compliance with the limits stated in the United States Pharmacopoeia is ensured by high-pressure homogenization, the final step of the manufacturing process. The US Food and Drug Administration’s Quality-by-Design approach requires a control strategy based on deep process understanding to ensure that products have a consistent and predefined quality. Here we investigated the process parameters of a jet-valve high-pressure homogenizer, specifically their effect on the MPD, pFAT5 value and droplet count (determined by microscopy) during the production of a Lipofundin MCT/LCT 20% formulation. We provide deep insight into droplet breakup and coalescence behavior when varying the process pressure, emulsion temperature and number of homogenization cycles. We found that high shear forces are not required to reduce the pFAT5 value of the particle distribution. Finally, we derived a control strategy for a rapid and cost-efficient two-cycle process that ensures patient safety over a large control space.

Application of multi-parametric characterization to water-based fire suppression systems in compartment fire scenarios

A new predictive fire suppression model has been developed and applied to a compartment room environment with various fire locations to clarify the suppression mechanisms of water mist and sprinkler systems. To effectively mitigate the combustion process, an in-depth framework has been developed, which includes the thermal fluidic interactions and utilizes statistical approaches for water droplets characterization. Efficiencies and effectiveness of both systems under different operating conditions were investigated with a multi-parametric approach that uniquely traces the accumulative mass fluxes, penetrability and number counts of droplets. Different fire suppression scenarios were identified based on combustion behaviors, and the suppression systems’ performance was evaluated based on spray coverage, penetrability, water utilization rate and potential water damage. The current study finds that water mist systems significantly outperform sprinkler systems in suppressing centered fires from both time (within 0.55 s) and utilization rate (up to 6.78%) perspective, while sprinkler systems can effectively suppress fires within a larger area, but their water utilization rate is as low as 0.07%. For water mist systems, although the water utilization rate can be 37 times higher than sprinkler systems, their effective suppression coverage area is small, which provided directions for future improvement.

Co-administration of drugs with parenteral nutrition in the neonatal intensive care unit—physical compatibility between three components

There is a lack of compatibility data for intravenous therapy to neonatal intensive care unit (NICU) patients, and the purpose of this study was to contribute with documented physical compatibility data to ensure safe co-administration. We selected Numeta G13E, the 3-in-1 parenteral nutrition (PN) used at our NICU, together with the frequently used drugs morphine, dopamine and cefotaxime in two- but also three-component combinations. Incompatibility may lead to particle formation (precipitation) and oil-droplet growth (emulsion destabilisation), both which are undesirable and pose a safety risk to already unstable patients. We assessed potential particle formation of three mixing ratios for each combination (always including 1 + 1 ratio) using light obscuration, turbidity and pH measurements combined with visual inspection by focused Tyndall beam. Potential droplet-growth and emulsion destabilisation was assessed by estimating PFAT5 from droplet size measurements and counts, mean droplet diameter and polydispersity index from dynamic light scattering, and pH measurements. Mixed samples were always compared to unmixed controls to capture changes as a result of mixing and samples were analysed directly after mixing and after 4 h to simulate long contact time. None of the samples showed any sign of precipitation, neither in the drug-drug nor in the two- or three-component mixture with PN. Neither did we detect any form of emulsion destabilisation.Conclusion: Dopamine, morphine and cefotaxime were found to be compatible with NumetaG13E, and it is safe to co-administer these drugs together with this PN in NICU patients.What is Known:• The need for co-administration of drugs and complex PN admixtures occurs frequently in NICU due to limited venous access.• Available compatibility data are scarce and for combinations of more than two components non-existent.What is New:• Here we report physical compatibility data of two- as well as three-component combinations of frequently used NICU drugs and a 3-in-1 PN admixture.• Co-administration of Numeta G13E with dopamine and morphine, but also with morphine and cefotaxime is safe in NICU.

The Bovine Hepatic Cell Line BFH12 as a Possible Model for Hepatosteatosis in Dairy Cows.

Hepatosteatosis is a common metabolic disorder of dairy cows, especially during early lactation. Currently, there are a few models of bovine hepatic steatosis available, including primary hepatocytes, liver slices, and animal models. Studies that elucidate the influence of single fatty acids on lipid classes, fatty acid pattern, gene expression, and phenotypic changes are still limited. Hence, we investigated the suitability of the fetal bovine hepatocyte-derived cell line BFH12 as a model for hepatosteatosis. To create a steatotic environment, we treated BFH12 with stearic acid, palmitic acid, or oleic acid in non-toxic doses. Thin-layer chromatography and gas chromatography were used to analyze lipid classes and fatty acid pattern, and qPCR was used to quantify gene expression of relevant target genes. Lipid droplets were visualized with confocal laser scanning microscopy and evaluated for number and size. Treatment with oleic acid increased triglycerides, as well as lipid droplet count per cell and upregulated carnitine palmitoyl transferase 1, which correlates with findings of in vivo models. Oleic acid was largely incorporated into triglycerides, phospholipids, and non-esterified fatty acids. Stearic acid was found mainly in non-esterified fatty acids and triglycerides, whereas palmitic acid was mainly desaturated to palmitoleic acid. All three fatty acids downregulated stearyl-CoA-desaturase 1. In conclusion, BFH12 can acquire a steatotic phenotype by incorporating and accumulating fatty acids. Oleic acid is particularly suitable to produce hepatosteatosis. Therefore, BFH12 may be a useful in vitro model to study bovine hepatosteatosis and its underlying molecular mechanisms.