Capture Area Research Articles

Hydroxide Exchange Membrane Carbon Capture (HEMCC) Using Nickel Hydroxide Batteries and Flow-through Membranes

Proposed is an electrochemical nickel hydroxide based hydroxide exchange membrane carbon capture (HEMCC) device for Direct Air Capture (DAC) of CO2. DAC has been identified as one of the key net negative carbon technologies to achieve net zero carbon emissions. Net negative carbon technologies are required to offset continued emissions from dilute CO2 sources such as agriculture and construction. The majority of current DAC technologies at scale (>1 KT∙yr-1) are adsorbent based technologies with significant energy cost. The traditional DAC energy cost is primarily driven by the temperature swing required to regenerate the sorbent and has been shown to be 1.8 MWh·ton-1 at the system level.Electrochemical pH swing devices are a growing research area for carbon capture devices with the goal of lowering the energy cost required for DAC. A pH gradient is built by generating OH- at the cathode and consuming OH- at the anode. An acid-base equilibrium with CO2 allows for the capture of CO2 at the cathode and release at the anode. This extends from other electrochemical CO2 capture devices based on pKa shifts of an electrochemically active organic species allowing for the capture and release of CO2. Electrochemical CO2 capture is considered promising based on potentially low energy costs to capture CO2 in comparison with current temperature swing adsorption technologies.This work explores Ni(OH)2 electrodes to produce the pH gradient for CO2 capture and release. At the cathode NiOOH is reduced to Ni(OH)2 while at the anode Ni(OH)2 is oxidized to NiOOH. The symmetrical electrodes allow for a low voltage requirement; the thermodynamic potential difference of standard electrochemical reactions is zero. Most of the voltage observed is to produce the pH gradient with the remainder driving the polarization of the electrodes. There is a resistance component as well, but this is small in comparison due to the low current densities used in the device, nominally 2 mA·cm-1.Two similar devices are presented, a traditional MEA (membrane electrode assembly) and a flow-through MEA. The traditional MEA separates the two Ni(OH)2 electrodes with an 80μm Piperion® membrane. While the flow-through membrane separates the electrodes with a three piece membrane consisting of two 80μm Piperion® membranes with a porous membrane between them. In the traditional MEA system air is passed over the cathode for capture, while the flow-through MEA the air is passed through the porous membrane isolated from the electrodes.The traditional MEA has been used to establish a baseline performance of the device and has been shown to capture CO2 at an energy cost of 1 MWh·ton-1 at the device level. An understanding has been built around the components of that energy cost including the relationship of flux to current density, effect of a regeneration process, transient battery behavior, and gas losses coinciding with changing the polarization of the batteries.The flow-through MEA looks to address of transient battery behavior and gas losses. It allows for denser, higher capacity electrodes, which can lean on traditional Ni-MH battery technology used in alkaline batteries used today. The higher capacities, limit the transient battery effect on flux in the device. Gas losses are addressed by having a continuous inlet air stream to the device and continuous outlet product.

Abstract C025: Identification of cell-cell signaling programs across the tumor-tumor microenvironment ecosystem and associated with clinical status in neoadjuvant osimertinib treated patient samples revealed by spatial profiling

Abstract Lung cancer is the leading cause of cancer mortality, and despite improvements in treatment, tumors typically respond incompletely and resume growth after acquisition of drug resistance. Recent completion of a neoadjuvant osimertinib Phase II trial treating patients with surgically resectable stage I-IIIA EGFR-mutated non-small cell lung cancer (EGFRm NSCLC) (NCT03433469) (Blakely et. Al, JCO 2024) has highlighted the importance of further identifying non-genomic mechanisms of persistence and resistance to targeted therapy. Here we analyzed these patient samples to identify transcriptionally regulated signaling patterns enriched at Residual Disease (RD) after neoadjuvant osimertinib treatment compared to treatment naïve samples (TN), as well as signaling patterns enriched at RD in patients who ultimately develop disease recurrence after surgical resection compared to those who remain disease-free. Spatially resolved transcriptomic sequencing was performed, using the 10X Genomics Visium platform, on 36 tissue sections (n=9 TN, n=19 RD, n=4 Progressive Disease (PD), n=4 Tumor Adjacent Normal), from 25 patients. TN and PD samples were from standard-of-care surgical resections. 18 of 19 RD samples were from NCT03433469. The Visium array spots that tile the sequencing capture area are 55 µm in diameter, and thus can contain an estimated 1-10 cells within each array spot. After quality control, 91,582 array spots remained for downstream analysis. We identified high confidence tumor array spots annotated both as “Cancer” by a board-certified pathologist and with tumor characteristic copy number variations. Through dimensionality reduction clustering, we identified 10 major array spot clusters, including the high confidence tumor array spot cluster. These clusters were further subset into 44 high resolution clusters of array spot niches, 32 of which were shared across at least nine patients. Because array spots are not single-cell resolution, these niches represent spots with similar mixed cell type composition and transcriptional signatures. We identified significant increases in the CCL14+ Endothelial Cell Niche, CXCL2+ Endothelial Cell Niche, Lymphocytes + Endothelial Niche, and CXCL12+ Fibroblast Niche in RD samples compared to TN. We identified a cell signaling program defined by spatially co-expressed ligand-receptor pairs associated with focal adhesion, enriched in PD samples. This same pattern was enriched in RD samples from patients who had recurrent disease after surgical resection compared to RD samples from patients who remained disease free. These data describe an increase in immune trafficking in RD samples, as well as identify an EGFR- alternative signaling pathway correlating with osimertinib resistance. Identification of spatially resolved, differential architectural organization and signaling patterns in RD and PD states will expand our understanding of targeted therapy resistance in EGFRm NSCLC, with the potential to identify additional clinically actionable targets. Citation Format: Whitney Tamaki, Daniel L. Kerr, Wei Wu, Grant Eilers, Anatoly Urisman, Yu-Ting Chou, Philippe Gui, Shigeki Nanjo, Johannes R. Kratz, David M. Jablons, Trever G. Bivona, Collin M. Blakely. Identification of cell-cell signaling programs across the tumor-tumor microenvironment ecosystem and associated with clinical status in neoadjuvant osimertinib treated patient samples revealed by spatial profiling [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr C025.

Integrating gene expression and imaging data across Visium capture areas with visiumStitched

BackgroundVisium is a widely-used spatially-resolved transcriptomics assay available from 10x Genomics. Standard Visium capture areas (6.5mm by 6.5mm) limit the survey of larger tissue structures, but combining overlapping images and associated gene expression data allow for more complex study designs. Current software can handle nested or partial image overlaps, but is designed for merging up to two capture areas, and cannot account for some technical scenarios related to capture area alignment.ResultsWe generated Visium data from a postmortem human tissue sample such that two capture areas were partially overlapping and a third one was adjacent. We developed the R/Bioconductor package visiumStitched, which facilitates stitching the images together with Fiji (ImageJ), and constructing SpatialExperiment R objects with the stitched images and gene expression data. visiumStitched constructs an artificial hexagonal array grid which allows seamless downstream analyses such as spatially-aware clustering without discarding data from overlapping spots. Data stitched with visiumStitched can then be interactively visualized with spatialLIBD.ConclusionsvisiumStitched provides a simple, but flexible framework to handle various multi-capture area study design scenarios. Specifically, it resolves a data processing step without disrupting analysis workflows and without discarding data from overlapping spots. visiumStitched relies on affine transformations by Fiji, which have limitations and are less accurate when aligning against an atlas or other situations. visiumStitched provides an easy-to-use solution which expands possibilities for designing multi-capture area study designs.

Numerical investigation of the distributed combustion in the thermal choked solid fuel combined cycle engine

In this study, a solid fuel combined cycle engine concept based on the distributed combustion and the self-adaptive thermal choking is proposed, which can operate effectively within a wide Mach number range. By regulating the heat release through the distributed fuel injection, the thermal choking can be formed in the fixed geometry combustor. The air intake controls the flow capture and circulation area through the movement of its head cone, ensuring stable air breathing over a wide range. Numerical simulations conducted under Ma = 3.0 and 6.0 conditions using the validated Eulerian-Lagrangian method coupled with gaseous and particle reaction models demonstrate the concept's capability to operate within the Mach number range of 3.0–6.0, delivering improved mixing, combustion, and specific impulse performance.

The positive F wave in lead V1 of typical atrial flutter is caused by activation of the right atrial appendage: Insight from mapping during entrainment from the right atrial appendage.

Typical atrial flutter (AFL) is a macroreentrant tachycardia in which intracardiac conduction rotates counterclockwise around the tricuspid annulus. Typical AFL has specific electrocardiographic characteristics, including a negative sawtooth-like wave in the inferior lead and a positive F wave in lead V1. This study aimed to analyze the origin of the positive F wave in lead V1, which has not been completely understood. This study enrolled 10 patients who underwent radiofrequency catheter ablation for a typical AFL. Electroanatomical mapping was performed both during typical AFL and entrainment from the right atrial appendage (RAA). The 12-lead electrocardiogram (ECG) and three-dimensional (3D) electroanatomical maps were analyzed. The positive F wave in lead V1 changed during entrainment from the RAA in all the cases. The 3D map during entrainment from the RAA revealed an area of antidromic capture around the RAA, which collided with the orthodromic wave in the anterior right atrium. This area of antidromic capture around the RAA was the only difference from the 3D electroanatomical map of AFL and is considered the cause of the change in the F wave in lead V1 during entrainment. The analysis of the differences in the 12-lead ECG and 3D maps between tachycardia and entrainment from the RAA clearly demonstrated that activation around the RAA is responsible for the generation of the positive F wave in lead V1 of typical AFL.

An initial game-theoretic assessment of enhanced tissue preparation and imaging protocols for improved deep learning inference of spatial transcriptomics from tissue morphology.

The application of deep learning to spatial transcriptomics (ST) can reveal relationships between gene expression and tissue architecture. Prior work has demonstrated that inferring gene expression from tissue histomorphology can discern these spatial molecular markers to enable population scale studies, reducing the fiscal barriers associated with large-scale spatial profiling. However, while most improvements in algorithmic performance have focused on improving model architectures, little is known about how the quality of tissue preparation and imaging can affect deep learning model training for spatial inference from morphology and its potential for widespread clinical adoption. Prior studies for ST inference from histology typically utilize manually stained frozen sections with imaging on non-clinical grade scanners. Training such models on ST cohorts is also costly. We hypothesize that adopting tissue processing and imaging practices that mirror standards for clinical implementation (permanent sections, automated tissue staining, and clinical grade scanning) can significantly improve model performance. An enhanced specimen processing and imaging protocol was developed for deep learning-based ST inference from morphology. This protocol featured the Visium CytAssist assay to permit automated hematoxylin and eosin staining (e.g. Leica Bond), 40×-resolution imaging, and joining of multiple patients' tissue sections per capture area prior to ST profiling. Using a cohort of 13 pathologic T Stage-III stage colorectal cancer patients, we compared the performance of models trained on slide prepared using enhanced versus traditional (i.e. manual staining and low-resolution imaging) protocols. Leveraging Inceptionv3 neural networks, we predicted gene expression across serial, histologically-matched tissue sections using whole slide images (WSI) from both protocols. The data Shapley was used to quantify and compare marginal performance gains on a patient-by-patient basis attributed to using the enhanced protocol versus the actual costs of spatial profiling. Findings indicate that training and validating on WSI acquired through the enhanced protocol as opposed to the traditional method resulted in improved performance at lower fiscal cost. In the realm of ST, the enhancement of deep learning architectures frequently captures the spotlight; however, the significance of specimen processing and imaging is often understated. This research, informed through a game-theoretic lens, underscores the substantial impact that specimen preparation/imaging can have on spatial transcriptomic inference from morphology. It is essential to integrate such optimized processing protocols to facilitate the identification of prognostic markers at a larger scale.

Dielectric modulation-based biomolecule detection using III-V vertical source-all-around tunnel FET

We present a dielectric modulation-based label-free biosensor utilizing a GaAsSb/GaSb heterojunction in a source-all-around vertical tunnel FET (TFET) configuration. The TFET, enhanced with a heavily doped source pocket and a metal core, exhibits improved gate control, current ratio, and subthreshold swing (SS). This novel design is evaluated for its sensitivity to biomolecules with various dielectric constants (5.5, 7.5, 10, and 12) through extensive TCAD simulations. Sensitivity analysis is conducted for different nanogaps, fill factors, and biomolecule charges (neutral, positive, and negative). The wide tunneling area provided by this source-all-around structure significantly increases the biomolecule capture area, resulting in superior sensitivity compared to other devices. Thus, the proposed TFET demonstrates excellent potential for diverse biomolecule detection applications.

An embedded gate gate-all-around FinFET for biosensing application

A dielectric modulated embedded gate gate-all-around fin field-effect transistor (EGGAA-FinFET) has been proposed for label-free detection applications of biomolecules in this article. The design expands the biomolecule capture area by establishing a cavity below the embedded gate. The performance of EGGAA-FinFET and FinFET biosensors is analyzed in a comprehensive comparison in terms of electrical performance, sensitivity and selectivity. Some important biosensing characteristics for EGGAA-FinFET (FinFET) have been calculated to be 0.43 V (0.32 V) for threshold voltage sensitivity, 2.22 × 106 (8.32 × 104) for current switching ratio sensitivity, and 0.75 (0.65) for subthreshold swing sensitivity. To determine the optimal structure of the biosensor, the effect of structural parameters on sensitivity is investigated. In addition, the effect of the filling factor on the biosensor is considered. The real-world performance of biosensors is assessed using the linearity parameter, showing that the EGGAA-FinFET biosensor has better noise resistance compared to the FinFET biosensor.

Investigating the efficacy of foam-based dust particle capture for dust elimination in ore pass unloading: A similar experimental study

Dust pollution arising from ore unloading poses significant concerns for occupational health. The foam-based dust particle capture presents a promising solution for dust suppression due to enhanced wettability, broader dust capture area, and stronger adhesion. This study designed a similar experiment platform to investigate how unloading conditions and foam parameters influence airflow dynamics and dust migration. The results indicate that airflow intensity and dust source are pivotal factors affecting dust concentration. Additionally, applying foam at the unloading port on the first level or the ore bin proves effective. Foam-dust interaction duration and airflow intensity are crucial determinants of dust suppression efficacy. Furthermore, the study reveals that the foam has a dual effect on dust control: while it efficiently captures dust particles to mitigate pollution, it can also disrupt airflow unfavorably. This research offers valuable insights into optimizing the spatial arrangement and quantitative application parameters of foam equipment.

Investigating the Influence of Anthropogenic Activities on Behavioral Changes of an Orb Web Spider (Neoscona vigilans).

Orb web spiders are common and highly diversified animals found in almost all habitats. They have remarkable plasticity against biotic and abiotic factors, making them excellent indicators of environmental health. The web creation behavior of spiders is influenced by disturbances in the environment. The aim of this research was to observe the alteration in the web-building behavior of Neoscona vigilans caused by human activities, specifically traffic disturbances. Spider webs were located and photographed at nighttime along the roadside, and their web characteristics were calculated. Spiders were captured from webs for their body measurements. Spider fourth leg length, carapace width, and body length had a significant association with web size and diameter, CTL, capture area, and mesh size. The quantity of trapped prey, the height of the plant, and the foliage radius increased with the distance from the road. Conversely, anchor points and web elevation from the ground dropped. The highest and lowest proportions of anomalies (modifications/defects) were recorded as holes (52.7%) in 105 webs (100%) and supernumerary (0.7%) in 55 webs (52.4%), respectively. Road disturbance had a negative influence on the spider's behavior as the webs formed in close proximity to the road had a higher frequency of anomalies, with a gradual decrease distantly. We can gain further insight into how different environmental changes, disruptions, and pollutants lead to this imperfection in the otherwise flawless perfect structure of spider webs.

Integrating gene expression and imaging data across Visium capture areas with visiumStitched.

Visium is a widely-used spatially-resolved transcriptomics assay available from 10x Genomics. Standard Visium capture areas (6.5mm by 6.5mm) limit the survey of larger tissue structures, but combining overlapping images and associated gene expression data allow for more complex study designs. Current software can handle nested or partial image overlaps, but is designed for merging up to two capture areas, and cannot account for some technical scenarios related to capture area alignment. We generated Visium data from a postmortem human tissue sample such that two capture areas were partially overlapping and a third one was adjacent. We developed the R/Bioconductor package visiumStitched, which facilitates stitching the images together with Fiji (ImageJ), and constructing SpatialExperiment R objects with the stitched images and gene expression data. visiumStitched constructs an artificial hexagonal array grid which allows seamless downstream analyses such as spatially-aware clustering without discarding data from overlapping spots. Data stitched with visiumStitched can then be interactively visualized with spatialLIBD. visiumStitched provides a simple, but flexible framework to handle various multi-capture area study design scenarios. Specifically, it resolves a data processing step without disrupting analysis workflows and without discarding data from overlapping spots. visiumStiched relies on affine transformations by Fiji, which have limitations and are less accurate when aligning against an atlas or other situations. visiumStiched provides an easy-to-use solution which expands possibilities for designing multi-capture area study designs.

Research on the Method of Detecting TPN-Labeled Tumor Cells in Pleural Effusion Based on the Microfluidic Chip.

The clinical diagnosis of a malignant pleural effusion (MPE) is still based on the detection of tumor cells in the pleural effusion. The question of how to improve the efficiency and accuracy of detecting an MPE still remains. This study explores the use of microfluidic technology to concentrate cells in an MPE and achieved the detection of the cell marker TPN in the microarray capture area. TPN is a mitochondria-specific bio-probe that can identify tumor cells on the basis of differences in the mitochondrial potential. First, we designed a microfluidic chip to analyze its performance. The results show that when the total flow rate of the injected chip was 12 mL/h and the volume ratio of cell separation liquid to cell suspension was 1:1, the target cells (A549, MCF-7, and Hela) were enriched and the purity was improved to 98.7-99.3%. Finally, an MPE from cancer patients was used to detect the chip's ability to isolate and enrich tumor cells. Furthermore, the fluorescent identification of the TPN within the tumor cells was simultaneously achieved on the microfluidic chip. In conclusion, the potential to improve the efficiency of the clinical diagnosis of MPEs is provided by the chip structure and analysis conditions explored in this study.

Overlapping Areas Used for Artisanal Fishing and Populations of Franciscana Dolphin (Pontoporia blainvillei) in the Southwest Atlantic Ocean

This study identified the overlap between artisanal fishing areas and the Franciscana dolphin (Pontoporia blainvillei) in the Southwest Atlantic Ocean (SWAO), Brazil, to identify areas where the species was incidentally captured from the perception of artisanal fishers. Using a semistructured questionnaire, ethnographic interviews (n = 330) were carried out from 2012 to 2018 with fishers from ten communities in southeastern (ES and RJ) and southern (PR) Brazil. After the interviews, the fishers presented their fishing routes, locations and areas of incidental capture and occurrence of the Franciscana dolphin. Ninety-five fishers (29%) identified the species: 23 in northern ES, 1 in southern ES, 20 in northern RJ, and 51 in the PR. Among the 235 fishers who could not identify the species, approximately half worked in the distribution gaps. The areas of occurrence noted by the fishers coincided with those described in the “National Action Plan for the Conservation of the Toninha,” an official document from the Brazilian Government and scientific literature. The results indicate that the information provided by fishers is useful for understanding the distribution of the Franciscana dolphin and can be used in the development of management strategies to mitigate the incidental capture of the species.

Unsteady flow characteristics in an over-under TBCC inlet during mode transition under unthrottled and throttled conditions

The study presents an experimental exploration into the mode transition of an over-under TBCC (Turbine-Based Combined Cycle) inlet, with a specific emphasis on the flow characteristics at off-design transition Mach number. A systematic investigation was undertaken into the mode transition characteristics in both unthrottled and throttled conditions within a high-speed duct, employing high speed Schlieren and dynamic pressure acquisition systems. The results show that the high-speed duct faced flow oscillations primarily dictated by the separation bubble near the duct entrance during the downward rotation of splitter, leading to the duct’s unstart under the unthrottled condition. During the splitter’s reverse rotation, a notable hysteresis of unstart/restart of the high-speed duct was observed. Conversely, hysteresis vanishes when the initial flowfield nears the critical state owing to downstream throttling. Moreover, the oscillatory diversity, a distinctive characteristic of the high-speed duct, was firstly observed during the mode transition induced by throttling. The flow evolution was divided into four stages: an initial instability stage characterized by low-frequency oscillations below 255 Hz induced by shock train self-excitation oscillation and high-frequency oscillations around 1367 Hz caused by the movement of separation bubble. This stage is succeeded by the “big buzz” phase, comprised of pressure accumulation/release within the overflow-free duct and shock motion outside the duct to retain dynamic flow balance. The dominant frequency escalated with the increase of the internal contraction ratio in the range of 280 Hz to 400 Hz. This was followed by a high-frequency oscillation stage around 453 Hz dominated by a large internal contraction ratio with low pulsating energy, accompanied by a continuous supersonic overflow. Lastly, as the splitter gradually intersected the boundary layer of the first-stage compression surface, the capture area and the turbulence intensity of the incoming flow underwent a sudden shift, leading to a more diverse flow oscillation within the duct, manifested as various forms of mixed buzz.

Anomaly Detection and Biomarkers Localization in Retinal Images.

Background: To design a novel anomaly detection and localization approach using artificial intelligence methods using optical coherence tomography (OCT) scans for retinal diseases. Methods: High-resolution OCT scans from the publicly available Kaggle dataset and a local dataset were used by four state-of-the-art self-supervised frameworks. The backbone model of all the frameworks was a pre-trained convolutional neural network (CNN), which enabled the extraction of meaningful features from OCT images. Anomalous images included choroidal neovascularization (CNV), diabetic macular edema (DME), and the presence of drusen. Anomaly detectors were evaluated by commonly accepted performance metrics, including area under the receiver operating characteristic curve, F1 score, and accuracy. Results: A total of 25,315 high-resolution retinal OCT slabs were used for training. Test and validation sets consisted of 968 and 4000 slabs, respectively. The best performing across all anomaly detectors had an area under the receiver operating characteristic of 0.99. All frameworks were shown to achieve high performance and generalize well for the different retinal diseases. Heat maps were generated to visualize the quality of the frameworks' ability to localize anomalous areas of the image. Conclusions: This study shows that with the use of pre-trained feature extractors, the frameworks tested can generalize to the domain of retinal OCT scans and achieve high image-level ROC-AUC scores. The localization results of these frameworks are promising and successfully capture areas that indicate the presence of retinal pathology. Moreover, such frameworks have the potential to uncover new biomarkers that are difficult for the human eye to detect. Frameworks for anomaly detection and localization can potentially be integrated into clinical decision support and automatic screening systems that will aid ophthalmologists in patient diagnosis, follow-up, and treatment design. This work establishes a solid basis for further development of automated anomaly detection frameworks for clinical use.

Study of the Spatial Distribution of the Bark Beetle in the Ejido Tixtlancingo

The spatial distribution of Dendroctonus frontalis Zimmermann, 1868, and Dendroctonus mexicanus Hopkins, 1905, was determined from 2020 to 2021 in the Tixtlancingo ejido. The information came from two surveys because, despite the abundant forested areas in this geographical area of the state of Guerrero, Mexico, economic resources for pest biomonitoring are limited. However, it was possible to identify the presence of 76 outbreaks affecting 1117.697 hectares and 95,078 trees, totaling 14,223.8 m3 of standing timber volume. In 2020, 28 outbreaks were reported, with the eastern spatial distribution showing the most damage from bark beetles, particularly in outbreaks 7 and 14 of the surveyed area. The most affected conifers were Pinus maximinoi H. E. Moore (44.71%), Pinus oocarpa Schiede ex Schltdl. (39.93%), and Pinus pseudostrobus Lindl. (15.36%). The affected timber volume was observed in diameter categories of 30 cm for the three pine species, with infestation of 90,549 trees (13,497.6 m3 t.t.v. (total tree volume)) across 1057.64 hectares. In 2021, 48 outbreaks were recorded, with the northeastern and southern parts of the surveyed area showing the most damage from the bark beetle. The trees most affected by the bark beetle were P. oocarpa (59.17%), P. maximinoi (33.94%), and P. pseudostrobus (6.89%). It was observed that the affected volume occurred in trees with diameter categories of 50 cm for the three pine species, affecting 4529 trees (726.214 m3 t.t.v.) distributed over 60.06 hectares. The contribution of this work lies in establishing a baseline for monitoring damage caused by this beetle, which affects forest resources and diminishes the possibility of maintaining carbon capture areas in the medium and long term, thus impacting the Sustainable Development Goals (SDGs) of the 2030 agenda, specifically Goals 11, 13, and 15.

Numerical simulation of non-spherical microparticles' deposition on single fiber

As a classical gas-solid two-phase flow system, the processes of fiber filtering microparticles are prevalent in nature and engineering. However, the impact of microparticle shape on fiber filtration processes is still largely unexplored. Herein, using the self-developed spheropolyhedral-based discrete element lattice Boltzmann method, the filtration process of non-spherical microparticles through a single fiber is investigated. Results show that the single fiber efficiency (SFE) for non-spherical particles exhibits a trend of initially increasing and subsequently decreasing trend with the increase in Stokes number (St), which is similar to the case of spherical particles. However, it is interesting to note that the peak values of SFE increase significantly with decreasing particle sphericity (ψ) and the corresponding St values become larger. As ψ decreases from 1.0 (sphere) to 0.671 (tetrahedron), the SFE increase from 0.205 to 0.49 and the corresponding St rises from 1.0 to 1.75. The enhanced SFE can be explained by elevated collision probability and adhesion probability, based on detailed particle kinematics and dynamics behavior analysis as well as microscopic depositional structure evaluation. The depositional structures of the non-spherical particles have larger capture areas, leading to higher initial collision probabilities. Meanwhile, the anisotropic collisions between non-spherical particles and fibers greatly contribute to higher secondary collision probabilities. In addition, compared to spherical particles of the same volume, the non-spherical particles experience greater fluid resistance, resulting in lower initial collision velocities and larger initial adhesion probabilities. The face-to-face contacts between non-spherical particles also lead to stronger interparticle adhesion and enhanced adhesion probabilities.

Abstract 3768: Optimization of digital pathology through laser capture microdissection with a 405 nm laser

Abstract Tumor cellular heterogeneity is a complex problem in cancer molecular diagnostics and personalized therapy. The tumor is a product of the different types and interactions of host and immune cells. Investigators have created a variety of methods to procure separate subpopulations of the tumor microenvironment for individual analysis. One of the most successful methods of this is laser capture microdissection (LCM). This method captures specific subpopulations of cells under direct microscopic visualization. This LCM technology has successfully been used for over 20 years, revealing a variety of insights into cancer pathogenesis and mechanisms of therapeutic response employed in numerous clinical trials. Nevertheless, there are two drawbacks to the current systems. For UV cutting (365 nm), the tissue is significantly damaged by the UV light energy. Infrared (808 nm) laser systems do not damage the tissue however, this method has low power and poor resolution. Our first hypothesis to be tested is that a new class of near UV 405 nm laser will have small capture areas approaching single cells while simultaneously preventing cellular damage. The second weakness of LCM is the requirement for an open-faced tissue section without a coverslip. Moreover, when visualizing the tissue of interest, the identification of regions of interest is obscured due to the refractive index mismatch between the laser microdissection cap and the tissue surface. We hypothesize that using a volatile organic compound with a refractive index similar to glass would elucidate the tissue region of interest to allow proper visualization. We successfully developed and tested a near 405 nm wavelength LCM system that utilizes a “liquid” coverslip to visualize the sample of interest with higher clarity, resolution, and contrast for immunohistochemistry, immuno-fluorescence, blood smear slides, and conventional hematoxylin-eosin tissue staining. Overall, these critical improvements LCM technology now allow for single-cell tissue capture, system automation, tissue visualization, and opens the door for artificial intelligence-assisted spatial profiling. Citation Format: Thomas Philipson, Marissa Howard, Kevin Johnson, Amanda Still, Furkat Yunusov, Emanuel Petricoin, Virginia Espina, Noel Gonzalez, Alan Carpino, Lance Liotta. Optimization of digital pathology through laser capture microdissection with a 405 nm laser [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3768.

Abstract 1273: Tumor progression and tumor microenvironment of pancreas cancer ascites revealed by scRNA-seq and spatial transcriptomics

Abstract Peritoneal metastasis of pancreas cancer is one of the ultimate modes of spread in the cancer. Little is known about how cancer cells spread into abdominal cavity and what is different from hematogenous metastasis. It is also not well characterized how tumor microenvironment prevent cancer cells from spreading in abdominal cavity. We performed single-cell RNA-seq analysis and special transcriptomic analysis to clarify the progression and environment of the cancer. We collected and processed ascites samples of 20 PDAC samples from 19 patients. Sixteen ascites samples were obtained from abdominal paracentesis and two cases in the postmortem period. For one patient ascites was collected both pre and postmortem. All but one patient received chemotherapy prior to ascites collection. Routine clinical cytology evaluation of ascites samples from 17 patients indicated it was malignant in 11 patients and nonmalignant in six patients. All ascites samples were purified by gradient centrifuge using Ficoll-Paque Plus to remove erythrocytes and necrotic debris. For the platform, we adopted the 10x Genomics Chromium Single Cell Gene Expression platform for single-cell RNA-seq library preparation. Spatial transcriptomics was performed for eight FFPE samples from the two autopsy patients with paired cancer ascites using 10x Visium. The CytAssist was used to transfer transcripts of pre-sectioned and pre-stained tissues with 11 × 11 mm Visium Capture Area slides. The sample locations were metastatic tumors to bowel wall, rib bone, mesentery, iliac nerve, diaphragm, peritoneum, pelvis, and primary pancreas tumor. A total of 248,263 cells were analyzed in single-cell RNA-seq. Cell population in pancreas cancer ascites consisted of macrophages, lymphocytes, dendritic cells, plasma cells, plasmacytoid dendritic cells, mesothelial cells, and cancer cells. Cancer cells were detected in twelve samples whereas no cancer cells were detected in eight samples. Gene ontology and gene set enrichment analyses showed macrophages in ascites with cancer cells involved neutrophil activation while those in ascites without cancer cells retained antigen presentation capacity and inducing interferon gamma pathway. Mesothelial cells in ascites with cancer cells showed more apoptosis and lymphocyte proliferation while those in ascites without cancers cells triggered fibrosis and mitosis. These data suggest that macrophage and mesothelial cells could be categorized into anti-tumor cells and tumor associated cells. Ongoing investigations are exploring ligand-receptor relationships. We are going to compare the expression profile of tumor cells in ascites fluid and in tissue from various organs by integrating single cell RNA-seq data and special transcriptomics data. Citation Format: Shigeaki Umeda, Elias-Ramzey Karnoub, Fiyinfolu Balogun, Alejandro Jiménez-Sánchez, Christine A. Iacobuzio-Donahue. Tumor progression and tumor microenvironment of pancreas cancer ascites revealed by scRNA-seq and spatial transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1273.

Rainwater harvesting as a sustainable solution for the production of urban hydroponic crops

ABSTRACT Population growth and poor agricultural practices demand an improvement in the efficiency of food production. Urban hydroponic crops represent a potential solution to this challenge. However, the use of drinking water for urban agriculture is not a priority. Consequently, rainwater harvesting can reduce the use of drinking water for other purposes than human consumption. This study evaluated the efficiency of rainwater harvesting for the production of hydroponic crops in an Andean city. We developed a rainwater harvesting model to analyze the efficiency and optimization of two hydroponic production scenarios: (1) domestic production (30 plants) and (2) small-scale commercial production (200 plants). We found an efficiency of 99.71 and 75.79%, for scenarios 1 and 2, respectively. The 75.79% efficiency is given by the presence of low precipitation periods, which in the case of the study area are sporadic. Furthermore, scenario 2 could reach efficiencies of 100% if the roof capture area increases up to 40 m2. Rainwater harvesting in Andean cities, with sustained precipitation throughout the year, is enough to supply water for domestic and small-scale commercial hydroponic production with basic household modifications. We show promising results by combining rainwater harvesting and hydroponic crops for improving urban food and water security.