Parallel Bulk Research Articles

Deciphering the senescence-based tumoral heterogeneity and characteristics in pancreatic cancer: Results from parallel bulk and single-cell transcriptome data.

The prevalent intra- and intertumoral heterogeneity results in undesirable prognosis and therapy failure of pancreatic cancer, potentially resulting from cellular senescence. Herein, integrated analysis of bulk and single-cell RNA-seq profiling was conducted to characterize senescence-based heterogeneity in pancreatic cancer. Publicly available bulk and single-cell RNA sequencing from pancreatic cancer patients were gathered from TCGA-PAAD, PACA-AU, PACA-CA, and GSE154778 datasets. The activity of three senescence-related pathways (cell cycle, DNA repair, and inflammation) was scored utilizing ssGSEA algorithm. A series of functional verifications of crucial genes were accomplished in patient tissue and pancreatic cancer cells. Based upon them, unsupervised clustering analysis was executed to classify pancreatic cancer samples into distinct senescence-based clusters at the bulk and single-cell levels. For single-cell transcriptome profiling, cell clustering and annotation were implemented, and malignant cells were recognized utilizing infercnv algorithm. Two senescence-based clusters were established and highly reproducible at the bulk level, with the heterogeneity in prognosis, clinicopathological features, genomic CNVs, oncogenic pathway activity, immune microenvironment and immune checkpoints. Senescence-relevant gene CHGA, UBE2C and MCM10 were proved to correlate with the migration and prognosis of pancreatic cancer. At the single-cell level, seven cell types were annotated, comprising ductal cells 1, ductal cells 2, fibroblasts, macrophages, T cells, stellate cells, and endothelial cells. The senescence-based classification was also proven at the single-cell level. Ductal cells were classified as malignant cells and non-malignant cells. In the tumor microenvironment of malignant cells, hypoxia and angiogenesis affected senescent phenotype. The heterogeneity in senescence was also observed between and within cell types. Altogether, our findings unveil that cellular senescence contributes to intra- and intertumoral heterogeneity in pancreatic cancer, which might facilitate the development of therapeutics and precision therapy in pancreatic cancer.

Amino acid carbon isotope profiles provide insight into lability and origins of particulate organic matter

AbstractIdentifying the phytoplankton origin of particulate organic matter (POM) in the deep ocean is challenging due to the changing phytoplankton composition and varied extent of decomposition by heterotrophic bacteria and zooplankton. Here, we report vertical distributions of amino acid stable carbon isotope values (δ13C) measured in particles in the South China Sea. Carbon‐weighted amino acid δ13C values generally parallel bulk POM δ13C profiles with a positive offset from 2.4‰ in the surface water to 6.0‰ in deep. Accordingly, a lability model is introduced to describe the relative distribution and isotopic linkage of labile and refractory particulate organic carbon. Temporal changes of amino acid δ13C were observed during the microbial decomposition of two phytoplankton strains, the prokaryote cyanobacterium Synechococcus and the eukaryote diatom Thalassiosira weissflogii. Principal component analysis of individual amino acid δ13C values from the decomposing cells separate samples into two components, reflecting the influence of microbial decomposition and taxonomic differences, respectively. These two components were further applied to particles. A major contribution from decomposing phytoplankton to particles below the euphotic zone was observed, with more prokaryote organic matter in the basin and a larger contribution from eukaryotes at stations near the productive northern shelf. Our findings show the applicability of amino acid δ13C values in tracing the lability and phytoplankton origins of POM in samples with varied extents of decomposition in marine environments.

Abstract B041: Defining the Determinants of Immune Response in DNA Homologous Recombination Deficient Tumors

Abstract Immune checkpoint blockade (ICB) has shown unprecedented success in improving clinical outcomes for numerous cancer patients, but many patients still fail to respond to treatment. Studies have demonstrated that the tumor microenvironment, tumor mutational burden, and patient DNA Damage Repair (DDR) deficiency may play a key role in determining response to ICB. To better characterize this and define key determinants of ICB response, we created an isogenic knockout BRCA2 in a murine 4T1 metastatic TNBC background to model these differential clinical responses and to assess how these tumor-intrinsic programs influence the tumor immune microenvironment to poise tumors for immunotherapy response. Differential immune landscapes were found via scRNAseq at baseline and with ICB driven by tumor DDR status with notable differences in the myeloid compartment and CXCR3-expressing T cell, NK, pDC, DCs, and plasma cells. Differential expression and interferon stimulated gene (ISG) metagene analysis showed notable differences in ISG expression in DDR-deficient samples at baseline, particularly in clusters containing monocytes and macrophages. Additionally, differential expression of CXCL10 in monocytes/macrophages and assessment of ligand-receptor interactions by CellChat similarly showed enhanced contribution CXCL10-CXCR3. Parallel bulk RNAseq analysis showed increased production of T cell trafficking chemokines that would poise the tumor for response to ICB. Our lab established a genetic interferon reporter system to measure both tumor intrinsic interferon-driven inflammation in cis and in trans with tumor associated macrophages, which enables multidimensional tracking of bidirectional signaling between tumor cells and macrophages by flow. This system enabled screening of inhibitors and tumor knockout cell lines to identify that tumor-intrinsic cGAS/STING and IFNb1 reinforce production of tumor and myeloid CXCL10/11 to poise the tumor for response to ICB. Further assessment of tumor cell lines via cellular fractionation experiments identified the presence of both gDNA and R-loops in the cytoplasm of BRCA2-mutant mammary cancer cell lines that may be detected as damage associated molecular patterns by tumor cells or myeloid cells in the tumor bed. Future studies aim at validating this DDR-driven production of IFNb1 as a driver of T cell chemokines in vivo; tumor-intrinsic knockout of IFNb1 and other T cell promoting chemokines (CXCL10/11/CCL5) to assess tumor or myeloid driven nature of this response to ICB and depletion of myeloid cells are being performed in parallel to assess contribution of tumor and myeloid cells, respectively. Taken together, our results have important implications for understanding the key drivers of ICB response in the tumor microenvironment and how patient-intrinsic mutations differentially poise the microenvironment for immunotherapy response. Citation Format: Natalie Vaninov, Robert Samstein. Defining the Determinants of Immune Response in DNA Homologous Recombination Deficient Tumors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B041.

MSIpixel: a fully automated pipeline for compound annotation and quantitation in mass spectrometry imaging experiments.

Mass spectrometry imaging (MSI) is commonly used to map the spatial distribution of small molecules within complex biological matrices. One of the major challenges in imaging MS-based spatial metabolomics is molecular identification and metabolite annotation, to address this limitation, annotation is often complemented with parallel bulk LC-MS2-based metabolomics to confirm and validate identifications. Here we applied MSI method, utilizing data-dependent acquisition, to visualize and identify unknown molecules in a single instrument run. To reach this aim we developed MSIpixel, a fully automated pipeline for compound annotation and quantitation in MSI experiments. It overcomes challenges in molecular identification, and improving reliability and comprehensiveness in MSI-based spatial metabolomics.

Impacts of wind flow across street-side building gaps on traffic pollutant dispersion at pedestrian level with different block heights

Urban neighborhoods, which contains numerous buildings and gaps between the buildings, are usually simplified as a single air-impermeable block in numerical simulations of urban air environments. Such a simplification reduces the computational costs but underestimates the pollutant removal capacity of the street, because the high-speed wind flow through the building gaps causes a flushing effect on pollutant distribution in the street. However, the influences of the gap flow on traffic pollutant dispersion remain unclear. Therefore, a four-way street network surrounded by four neighborhoods is assumed as a representative urban area, and the characteristics of the gap flow and its correlation with building height (H/W = 0.5–2, W = 30 m) are investigated numerically. The results show that the flow pattern within the street depends on the relative intensity of the flow across the gaps and the parallel bulk flow along the street. For lower (H/W = 0.5) or higher (H/W = 2) building heights, the gap flow is strong enough to break through the barrier of the bulk flow, and then enters the street to dilute the pollutants, causing the concentrations in the leeward region of the street to be lower than those in the windward region. Opposite results are found for medium building heights (H/W = 0.75–1.5), where the flow in the street is dominated by the parallel flow itself. The results also indicate that there exists a critical height, H/W = 1.5, below which the air environment is good in both the streets and neighborhoods.

Evidence of charge transfer in three-dimensional topological insulator/antiferromagnetic Mott insulator Bi1Sb1Te1.5Se1.5/α−RuCl3 heterostructures

We report magnetotransport measurements on ${\mathrm{Bi}}_{1}{\mathrm{Sb}}_{1}{\mathrm{Te}}_{1.5}{\mathrm{Se}}_{1.5}/{\mathrm{RuCl}}_{3}$ heterostructure nanodevices. ${\mathrm{Bi}}_{1}{\mathrm{Sb}}_{1}{\mathrm{Te}}_{1.5}{\mathrm{Se}}_{1.5}$ (BSTS) is a strong three-dimensional topological insulator (3D-TI) that hosts conducting topological surface states (TSS) enclosing an insulating bulk. $\ensuremath{\alpha}\text{\ensuremath{-}}{\mathrm{RuCl}}_{3}$ (namely, ${\mathrm{RuCl}}_{3}$) is an antiferromagnet that is predicted to behave as a Kitaev-like quantum spin liquid carrying chargeless Majorana excitations. Temperature ($T$)-dependent resistivity measurements on BSTS show the interplay between parallel bulk and surface transport channels. For $T<150$ K, surface state transport dominates over bulk transport. Multichannel weak antilocalization (WAL) is observed as a sharp cusp in the low-field magnetoconductivity, indicating strong spin-orbit coupling. The presence of top and bottom topological surface states (TSS) including a pair of electrically coupled Rashba surface states (RSS) is indicated. The nonlinear Hall effect, explained by a two-band model, further supports this interpretation. We observed that ${\mathrm{RuCl}}_{3}$ has an electrostatic effect on the TSS of BSTS, that is, it changes bandbending at the interface as a result of charge transfer. In this regard, the change in low-$T$ logarithmic resistivity upturn in the presence of out-of-plane magnetic field is analyzed employing the Lu-Shen model, supporting the presence of gapless surface states (TSS and RSS) with a $\ensuremath{\pi}$ Berry phase.

Parallel single-cell and bulk transcriptome analyses reveal key features of the gastric tumor microenvironment

BackgroundThe tumor microenvironment (TME) has been shown to strongly influence treatment outcome for cancer patients in various indications and to influence the overall survival. However, the cells forming the TME in gastric cancer have not been extensively characterized.ResultsWe combine bulk and single-cell RNA sequencing from tumors and matched normal tissue of 24 treatment-naïve GC patients to better understand which cell types and transcriptional programs are associated with malignant transformation of the stomach. Clustering 96,623 cells of non-epithelial origin reveals 81 well-defined TME cell types. We find that activated fibroblasts and endothelial cells are most prominently overrepresented in tumors. Intercellular network reconstruction and survival analysis of an independent cohort imply the importance of these cell types together with immunosuppressive myeloid cell subsets and regulatory T cells in establishing an immunosuppressive microenvironment that correlates with worsened prognosis and lack of response in anti-PD1-treated patients. In contrast, we find a subset of IFNγ activated T cells and HLA-II expressing macrophages that are linked to treatment response and increased overall survival.ConclusionsOur gastric cancer single-cell TME compendium together with the matched bulk transcriptome data provides a unique resource for the identification of new potential biomarkers for patient stratification. This study helps further to elucidate the mechanism of gastric cancer and provides insights for therapy.

Complex impedance, dielectric constant, electric modulus, and conductivity analysis of Cd doped ZnO nanostructures at high temperatures

Cd-doped zinc oxide (ZnO) nanostructures with a standard formulation Z n ( 1 − x ) C d x O (x = 0%, 3%, 6%, and 10%) were fabricated by a co-precipitation technique. The structural and morphological analyses were studied using x-ray diffraction (XRD) and scanning electron microscopy (SEM). The Study of x-ray diffraction investigation indorses the existence of a wurtzite structure with a P 6 3 mc space group in all the samples. Impedance spectroscopy, dielectric measurements, and electrical conductivity at different temperatures of 300–460 K with a frequency range from 20 Hz to 2 MHz were performed using an impedance LCR meter. The complex impedance spectrum ( Z ´ ´ v s Z ´ ) for all samples were fitted with a parallel bulk resistance ( R b ) and capacitance ( C b ) combination circuit. The results of the dielectric measurements indicate that the parameters ε ´ , ε ´ ´ , and tanδ are reduced with the increasing frequency and increase with temperature. The complex electric modulus plots ( M ´ , M ´ ´ ) with frequency have explained the non-Debye type of relaxations mechanism due to interfacial and depolarization. The variation of ac ( σ a c ) conductivity with Cd concentration indicates a gradual increase because the impedance values with Cd-doped decrease. It is confirmed that the activation energies decrease with the doping of Cd concentration. Moreover, ac conductivity was then investigated by Jonscher's power law. Finally, the temperature-dependent exponent s fitted well with the correlated barrier hopping (CHB) conduction. • Cd-doped ZnO nanoparticles with different concentrations were fabricated by the co-precipitation method. • XRD studies revealed the incorporation of Cd into ZnO lattice. • Nyquist plots suggested the negative temperature coefficient of resistance behaviour. • The influence of Cd-doping on the electrical behaviour of ZnO was reported.

High-plex expression profiling reveals that implants drive spatiotemporal protein production and innate immune activation for tissue repair

Surprisingly little clarity exists concerning effects of biomaterial properties on spatially localized protein expression, which drives implant success. Wound healing and tissue regeneration must be optimally supported by the implant, adsorbed proteins, immune cells, and fibroblasts; cells determine repair and functional recovery through protein production and regulation. However, not yet fully understood is how implants differentially drive spatial quantities of individual proteins both within the implant interior and the tissue surrounding it. Here we apply GeoMxⓇ digital spatial profiling to site-specifically investigate protein production in porous implants. Data is collected on the location and quantity of 40+ proteins from formalin-fixed, paraffin-embedded tissue slides of anisotropic tissue scaffolds (n = 18) with differing pore sizes (35 µm, 53 µm) and implantation durations (2, 14, 28 days); matching bulk gene expression data (700+ genes) is measured for identical implants. Notably, we discover fundamental spatial relationships in protein localization that in both the implant interior and the exterior are either uniquely independent or dependent of implant microstructure: dendritic cell marker CD11c and fibronectin significantly dominate the scaffold interior, while cell-to-cell adhesion marker CD34 and anti-inflammatory M2 polarization marker CD163 localize in the exterior. Lastly, collating spatial and bulk information, unique spatiotemporal expression patterns are identified for markers such as fibronectin, which are only uncoverable through spatial profiling and are otherwise hidden in bulk expression results. Together, these discoveries illustrate the critical importance of quantifying spatial expression patterns for implants, facilitating a paradigm shift in the iterative design, mechanistic understanding, and rapid assessment of biomaterials. Statement of significanceSpatial localization and expression of proteins, which determine implant success, are not fully understood because quantitative high-plex profiling is challenging. Applying GeoMxⓇ digital spatial profiling to site-specifically investigate protein production in porous implants, data is collected on the location and quantity of 40+ protein targets from tissue scaffolds with differing pore sizes (35 µm, 53 µm) and implantation durations (2, 14, 28 days). Collecting in parallel matched bulk gene expression data (700+ genes) for identical implants, we discover significant spatiotemporal expression patterns that remain otherwise hidden in differential bulk results. This new approach for the rapid assessment of biomaterials offers an enhanced mechanistic understanding and enables the tailoring of implants for superior regenerative outcomes.

Effect of C3H4O3 on Band Gap Narrowing of Proton Conductive Hybrid Polymer Electrolyte

AbstractIn the present work, hybrid polymer electrolyte based on carboxymethyl cellulose‐polyvinyl alcohol‐ammonium nitrate‐ethylene carbonate (CMC–PVA–NH4NO3–C3H4O3) become the promising materials that has demonstrated outstanding physical properties as an electrolytes system in solar cell. In the frame of solar cell progress, the electrical conductivity and optical bandgap of polymer electrolytes are equally explored. The characterization is carried out via electrical impedance spectroscopy (EIS) and ultraviolet visible‐near infrared (UV‐VIS‐NIR) spectroscopy. An equivalent circuit of parallel combination, bulk resistance (Rb), and constant phase element (CPE) is obtained from transparent conductive film, CMC–PVA–NH4NO3–C3H4O3. The optimum ionic conductivity is accomplished at 3.92 × 10−3 S cm‐1 for sample containing with 6 wt.% of C3H4O3. The absorption spectra are evaluated in the wavelength ranging from 200 to 1100 nm. Theoretical analysis reveals that the addition of 6 wt. % EC is initiating the band gap narrowing from 4.96 to 4.88 eV. The results show that the present developed materials‐based polymer electrolytes have great potential for solar energy devices.

Tunable plasmonic filter based on parallel bulk Dirac semimetals at terahertz frequencies.

A plasmonic bandpass filter based on parallel bulk Dirac semimetals (BDSs) is proposed and numerically investigated using the finite-difference time-domain method. The proposed filter is realized by the evanescent coupling between the resonator and waveguide, and Fabry-Parot resonant theory is used to analyze its realization mechanism. The performance of the filter can be tuned by changing the coupling distance, length of the resonator, and Fermi levels of the BDSs. We further simulate a plasmonic broadband filter using coupling mode splitting by locating two identical resonators along the waveguide direction. The pass band of the proposed broadband filter can be tuned by adjusting the coupling distances between the resonators and waveguide.

Magnesiothermic reduction kinetics of UF4

The most popular method for production of metallic uranium is by magnesiothermic reduction of UF4. Efficient production of good quality uranium metal chunk in the reaction vessel requires multiple parameter constraints. To theoretically optimize these process parameters, many basic properties, i.e. particle size, heat dissipation, packing density, heating rate, kinetic parameters of reaction, etc., are required. There was lack of information on kinetic parameters of this reaction; therefore, kinetic triplets of UF4 and magnesium metal reaction were determined by non-isothermal DTA method, at 5–20 K min−1 heating rates. The analysis of data was done by model-less methods and model-fitting methods. It was found that the reaction takes place through two parallel competitive mechanisms, bulk diffusion and first-order nucleation and growth of reaction sites, and the corresponding kinetic parameters, frequency factors and activation energies, were 440 min−1, 43.9 kJ mol−1, 420 min−1 and 49.03 kJ mol−1, respectively.

Criteria for Realizing Room-Temperature Electrical Transport Applications of Topological Materials.

The unusual electronic states found in topological materials can enable a new generation of devices and technologies, yet a long-standing challenge has been finding materials without deleterious parallel bulk conduction. This can arise either from defects or thermally activated carriers. Here, the criteria that materials need to meet to realize transport properties dominated by the topological states, a necessity for a topological device, are clarified. This is demonstrated for 3D topological insulators, 3D Dirac materials, and 1D quantum anomalous Hall insulators, though this can be applied to similar systems. The key parameters are electronic bandgap, dielectric constant, and carrier effective mass, which dictate under what circumstances (defect density, temperature, etc.) the unwanted bulk state will conduct in parallel to the topological states. As these are fundamentally determined by the basic atomic properties, simple chemical arguments can be used to navigate the phase space to ultimately find improved materials. This will enable rapid identification of new systems with improved properties, which is crucial to designing new material systems and push a new generation of topological technologies.

Automated mineralogy for quantification and partitioning of metal(loid)s in particulates from mining/smelting-polluted soils

Topsoils near active and abandoned mining and smelting sites are highly polluted by metal(loid) contaminants, which are often bound to particulates emitted from ore processing facilities and/or windblown from waste disposal sites. To quantitatively determine the contaminant partitioning in the soil particulates, we tested an automated mineralogy approach on the heavy mineral fraction extracted from the mining- and smelting-polluted topsoils exhibiting up to 1920 mg/kg As, 5840 mg/kg Cu, 4880 mg/kg Pb and 3310 mg/kg Zn. A new generation of automated scanning electron microscopy (autoSEM) was combined and optimized with conventional mineralogical techniques (XRD, SEM/EDS, EPMA). Parallel digestions and bulk chemical analyses were used as an independent control of the autoSEM-calculated concentrations of the key elements. This method provides faster data acquisition, the full integration of the quantitative EDS data and better detection limits for the elements of interest. We found that As was mainly bound to the apatite group minerals, slag glass and metal arsenates. Copper was predominantly hosted by the sulfides/sulfosalts and the Cu-bearing secondary carbonates. The deportment of Pb is relatively complex: slag glass, Fe and Mn (oxyhydr)oxides, metal arsenates/vanadates and cerussite were the most important carriers for Pb. Zinc is mainly bound to the slag glass, Fe (oxyhydr)oxides, smithsonite and sphalerite. Limitations exist for the less abundant contaminants, which cannot be fully quantified by autoSEM due to spectral overlaps with some major elements (e.g., Sb vs. Ca, Cd vs. K and Ca in the studied soils). AutoSEM was found to be a useful tool for the determination of the modal phase distribution and element partitioning in the metal(loid)-bearing soil particulates and will definitely find more applications in environmental soil sciences in the future.

Tunable Bragg reflector with parallel bulk Dirac semimetals at terahertz frequencies

We propose numerically a terahertz Bragg reflector with two parallel bulk Dirac semimetals (BDSs) sheets separated by alternated dielectric gratings using the finite-difference time-domain (FDTD) method. The transmission of the proposed reflector can be tuned via not only varying the permittivity of the dielectric grating but also changing the period number of the unit cells. By adjusting the separation distance of the parallel BDS sheets, we can derive another degree of freedom to tune the Bragg band gap. In addition, the transmission spectra can also be freely tuned by means of alkaline metal doping. At last, the defect resonant mode is realized in the Bragg reflector. Our proposed Bragg reflector will have potential prospects in designing integrated photonic circuits at terahertz frequencies.

The fate of O<sup>+</sup> ions observed in the plasma mantle: particle tracing modelling and cluster observations

Abstract. Ion escape is of particular interest for studying the evolution of the atmosphere on geological timescales. Previously, using Cluster-CODIF data, we investigated the oxygen ion outflow from the plasma mantle for different solar wind conditions and geomagnetic activity. We found significant correlations between solar wind parameters, geomagnetic activity (Kp index), and the O+ outflow. From these studies, we suggested that O+ ions observed in the plasma mantle and cusp have enough energy and velocity to escape the magnetosphere and be lost into the solar wind or in the distant magnetotail. Thus, this study aims to investigate where the ions observed in the plasma mantle end up. In order to answer this question, we numerically calculate the trajectories of O+ ions using a tracing code to further test this assumption and determine the fate of the observed ions. Our code consists of a magnetic field model (Tsyganenko T96) and an ionospheric potential model (Weimer 2001) in which particles initiated in the plasma mantle region are launched and traced forward in time. We analysed 131 observations of plasma mantle events in Cluster data between 2001 and 2007, and for each event 200 O+ particles were launched with an initial thermal and parallel bulk velocity corresponding to the velocities observed by Cluster. After the tracing, we found that 98 % of the particles are lost into the solar wind or in the distant tail. Out of these 98 %, 20 % escape via the dayside magnetosphere.

Multiplex gene transfer by genetic transformation between isolated S. pneumoniae cells confined in microfluidic droplets.

Gene exchange via genetic transformation makes major contributions to antibiotic resistance of the human pathogen, Streptococcus pneumoniae (pneumococcus). The transfers begin when a pneumococcal cell, in a transient specialized physiological state called competence, attacks and lyses another cell, takes up fragments of the liberated DNA, and integrates divergent genes into its genome. Recently, it has been demonstrated that the pneumococcal cells can be enclosed in femtoliter-scale droplets for study of the transformation mechanism, offering the ability to characterize individual cell-cell interactions and overcome the limitations of current methods involving bulk mixed cultures. To determine the relevance and reliability of this new method for study of bacterial genetic transformation, we compared recombination events occurring in 44 recombinants recovered after competence-mediated gene exchange between pairs of cells confined in femtoliter-scale droplets vs. those occurring in exchanges in parallel bulk culture mixtures. The pattern of recombination events in both contexts exhibited the hallmarks of the macro-recombination exchanges previously observed within the more complex natural contexts of biofilms and long-term evolution in the human host.

THE ROLE OF SHEAR STRESS IN THE GENERATION OF DEFINITIVE HAEMATOPOIETIC LINEAGES AND ARTERIAL VASCULATURE FROM HUMAN PLURIPOTENT STEM CELLS AT THE SINGLE-CELL LEVEL

This study aims to characterise the effect of fluid shear stress on human embryonic stem cell (hESC)-derived haematopoiesis and vasculogenesis by applying microfluidics, live cell imaging and single cell RNA sequencing. AGM-like haematopoietic cultures developed by Ng et al. were generated by manipulating WNT and TGFs signalling during mesoderm specification. The effect of pulsatile circulatory flow was studied in a microfluidic dynamic culture system, using SOX17 (Cherry)/RUNX1c(GFP) hESC line to read out arterial endothelial and haematopoietic differentiation, respectively. Microdevices generated cardiac-like, pulsatile flow in a circulatory culture system with a volume of 2–3µL. AGM-like haematopoietic development was observed by time-lapse imaging on chip for more than two weeks. We observed cells entering the circulation from the adherent layer, and the release of lightly tethered SOX17+ cells into the circulation. In parallel bulk differentiation culture using an orbital mixer to mimic the effect of wall shear stress, single cell RNA seq was performed on 8800 single cells at day 18 of culture. Control treatments were static culture and drug vehicle. Hierarchical cluster analysis identified 18 clusters belonging to erythroid-megakaryocytic, cardiovascular and myeloid differentiation pathways. We identified HOXA expressing mesenchymal cells in AGM cultures. Shear treatment promoted proliferative MYB, RUNX1, CD31 expressing blood progenitors, a reduced proportion of unipotent erythroid and megakaryocytic lineages, and increase numbers of myeloid and bipotent megakaryocyte-erythroid progenitors. The production of smooth muscle and cardiomyocytes was promoted by shear in non-AGM culture. This study demonstrates the feasibility of modelling human embryonic blood formation using microfluidic technology.

Investigation of LSM-YSZ Composite Cathode Performance Degradation with a Multistep Charge Transfer Model

The long-term performance degradation of LSM/YSZ composite cathodes is investigated via calibrated multiphysics simulation with a multistep oxygen reduction reaction (ORR) model and structural coarsening data from a phase field study. Multiphysics simulations, including a multistep ORR mechanism, are first developed for better understanding of the limiting processes in solid oxide fuel cells. The multistep ORR mechanism includes two parallel pathways, surface pathway and bulk pathway, which consist of elementary reaction steps. The multiphysics model is simultaneously calibrated with experimental polarization curves and impedance behavior for various air/fuel supply conditions. To our knowledge, this is the first time that a multistep ORR model is calibrated with such datasets. Next, the calibrated simulations are utilized to simulate a 2D half-cell constructed with measured microstructural data and random heterogeneity. Finally, the long-term performance degradation of the half-cell is predicted by the calibrated multiphysics model coupled with structural coarsening trends simulated using a phase field-based coarsening model. Degradation of both polarization curves and impedance behavior is investigated. Thorough analyses, including changes of contributions from different pathways, the resistance components, and overall reaction order, are performed to provide more insights into cathode performance degradation due to grain coarsening phenomena.

Accelerating next generation sequencing data analysis with system level optimizations

Next generation sequencing (NGS) data analysis is highly compute intensive. In-memory computing, vectorization, bulk data transfer, CPU frequency scaling are some of the hardware features in the modern computing architectures. To get the best execution time and utilize these hardware features, it is necessary to tune the system level parameters before running the application. We studied the GATK-HaplotypeCaller which is part of common NGS workflows, that consume more than 43% of the total execution time. Multiple GATK 3.x versions were benchmarked and the execution time of HaplotypeCaller was optimized by various system level parameters which included: (i) tuning the parallel garbage collection and kernel shared memory to simulate in-memory computing, (ii) architecture-specific tuning in the PairHMM library for vectorization, (iii) including Java 1.8 features through GATK source code compilation and building a runtime environment for parallel sorting and bulk data transfer (iv) the default ’on-demand’ mode of CPU frequency is over-clocked by using ’performance-mode’ to accelerate the Java multi-threads. As a result, the HaplotypeCaller execution time was reduced by 82.66% in GATK 3.3 and 42.61% in GATK 3.7. Overall, the execution time of NGS pipeline was reduced to 70.60% and 34.14% for GATK 3.3 and GATK 3.7 respectively.