Function Of Separation Research Articles

The rheology of interactions between leukocytes, platelets and the vessel wall in thrombo-inflammation.

Leukocytes and platelets must adhere to the wall of blood vessels to carry out their protective functions in inflammation and haemostasis. Recruitment is critically dependent on rheological variables (wall shear rate and stress, red cell aggregation and haematocrit) which affect delivery to the vessel wall as well as velocities and forces experienced there. Leukocyte recruitment is efficient only up to wall shear rates of about 300s-1 and usually restricted to low-shear post-capillary venules in inflammation. Being smaller, platelets experience lower velocities and shear forces adjacent to the wall and can adhere at much higher shear rates for haemostasis in arteries. In addition, we found quite different effects of variations in haematocrit or red cell aggregation on attachment of neutrophils or platelets, which also assist their separate recruitment in venules or arteries. However, it has become increasingly evident that inflammatory and thrombotic responses may occur together, with platelets promoting the adhesion and activation of neutrophils and monocytes. Indeed, it is 30 years since we demonstrated that platelets could cause neutrophils to aggregate in suspension and, when attached to a surface, could support selectin-mediated rolling of all leukocytes. Thrombin-activated platelets could further induce neutrophil activation and immobilisation. In some conditions, platelets could bind to intact endothelial monolayers and capture neutrophils or monocytes. Subsequently, we found that extracellular vesicles released by activated platelets (PEV) fulfilled similar functions when deposited on surfaces or bound to endothelial cells. In murine models, platelets or PEV could act as bridges for monocytes in inflamed vessels. Thus, leukocytes and platelets are rheologically adapted for their separate functions, while novel thrombo-inflammatory pathways using platelets or PEV may underlie pathogenic leukocyte recruitment.

An Unsupervised Machine Learning Approach for the Automatic Construction of Local Chemical Descriptors.

Condensing the many physical variables defining a chemical system into a fixed-size array poses a significant challenge in the development of chemical Machine Learning (ML). Atom Centered Symmetry Functions (ACSFs) offer an intuitive featurization approach by means of a tedious and labor-intensive selection of tunable parameters. In this work, we implement an unsupervised ML strategy relying on a Gaussian Mixture Model (GMM) to automatically optimize the ACSF parameters. GMMs effortlessly decompose the vastness of the chemical and conformational spaces into well-defined radial and angular clusters, which are then used to build tailor-made ACSFs. The unsupervised exploration of the space has demonstrated general applicability across a diverse range of systems, spanning from various unimolecular landscapes to heterogeneous databases. The impact of the sampling technique and temperature on space exploration is also addressed, highlighting the particularly advantageous role of high-temperature Molecular Dynamics (MD) simulations. The reliability of the resulting features is assessed through the estimation of the atomic charges of a prototypical capped amino acid and a heterogeneous collection of CHON molecules. The automatically constructed ACSFs serve as high-quality descriptors, consistently yielding typical prediction errors below 0.010 electrons bound for the reported atomic charges. Altering the spatial distribution of the functions with respect to the cluster highlights the critical role of symmetry rupture in achieving significantly improved features. More specifically, using two separate functions to describe the lower and upper tails of the cluster results in the best performing models with errors as low as 0.006 electrons. Finally, the effectiveness of finely tuned features was checked across different architectures, unveiling the superior performance of Gaussian Process (GP) models over Feed Forward Neural Networks (FFNNs), particularly in low-data regimes, with nearly a 2-fold increase in prediction quality. Altogether, this approach paves the way toward an easier construction of local chemical descriptors, while providing valuable insights into how radial and angular spaces should be mapped. Finally, this work opens the possibility of encoding many-body information beyond angular terms into upcoming ML features.

Asymmetric double-layer design of LiCl@CC/PAM for highly efficient water uptake from atmosphere

Water scarcity has become a global problem and caused a lot of conflicts. Atmospheric water harvesting (AWH) is a promising way to address water shortage issue. However, traditional adsorbent materials such as silica gels and zeolites suffer from low water productivity and high regeneration temperature. Hygroscopic salts like LiCl are regarded as a perspective substitution. Salt-modified metal organic frameworks (MOFs) and hydrogels are employed to alleviate the salt aggregation but they are limited to expensive fabrication or sluggish adsorption kinetics. Herein, we demonstrate an asymmetric double-layer design of LiCl@CC (carbon cloth)/PAM with separated function of water adsorption/desorption and water storage in different layer. This double-layer design not only enhances the mechanical properties but also shows an improved water adsorption kinetics compared to common salt-composite hydrogels. In experimental test, the LiCl@CC/PAM exhibits excellent water uptake of 1.5 g g−1 under 60 % RH in 4 h and fast water desorption under sunlight in 1.5 h. In outdoor test, LiCl@CC/PAM based device presents a daily water uptake of 5.12 g g−1 day−1. Meanwhile, all the materials used and fabrication process are feasible to scale up, which provides a possible solution to the global crisis of water scarcity.

Deep-Shallow Metaclassifier with Synthetic Minority Oversampling for Anomaly Detection in a Time Series

Anomaly detection in data streams (and particularly time series) is today a vitally important task. Machine learning algorithms are a common design for achieving this goal. In particular, deep learning has, in the last decade, proven to be substantially more accurate than shallow learning in a wide variety of machine learning problems, and deep anomaly detection is very effective for point anomalies. However, deep semi-supervised contextual anomaly detection (in which anomalies within a time series are rare and none at all occur in the algorithm’s training data) is a more difficult problem. Hybrid anomaly detectors (a “normal model” followed by a comparator) are one approach to these problems, but the separate loss functions for the two components can lead to inferior performance. We investigate a novel synthetic-example oversampling technique to harmonize the two components of a hybrid system, thus improving the anomaly detector’s performance. We evaluate our algorithm on two distinct problems: identifying pipeline leaks and patient-ventilator asynchrony.

Color-gradient-based phase-field equationfor multiphase flow.

In this paper, the underlying problem with the color-gradient (CG) method in handling density-contrast fluids is explored. It is shown that the CG method is not fluid invariant. Based on nondimensionalizing the CG method, a phase-field interface-capturing model is proposed which tackles the difficulty of handling density-contrast fluids. The proposed formulation is developed for incompressible, immiscible two-fluid flows without phase-change phenomena, and a solver based on the lattice Boltzmann method is proposed. Coupled with an available robust hydrodynamic solver, a binary fluid flow package that handles fluid flows with high density and viscosity contrasts is presented. The macroscopic and lattice Boltzmann equivalents of the formulation, which make the physical interpretation of it easier, are presented. In contrast to existing color-gradient models where the interface-capturing equationsare coupled with the hydrodynamic ones and include the surface tension forces, the proposed formulation is in the same spirit as the other phase-field models such as the Cahn-Hilliard and the Allen-Cahn equationsand is solely employed to capture the interface advected due to a flow velocity. As such, similarly to other phase-field models, a so-called mobility parameter comes into play. In contrast, the mobility is not related to the density field but a constant coefficient. This leads to a formulation that avoids individual speed of sound for the different fluids. On the lattice Boltzmann solver side, two separate distribution functions are adopted to solve the formulation, and another one is employed to solve the Navier-Stokes equations, yielding a total of three equations. Two series of numerical tests are conducted to validate the accuracy and stability of the model, where we compare simulated results with available analytical and numerical solutions, and good agreement is observed. In the first set the interfacial evolution equationsare assessed, while in the second set the hydrodynamic effects are taken into account.

Light quality-dependent roles of REVEILLE proteins in the circadian system.

Several closely related Myb-like activator proteins are known to have partially redundant functions within the plant circadian clock, but their specific roles are not well understood. To clarify the function of the REVEILLE 4, REVEILLE 6, and REVEILLE 8 transcriptional activators, we characterized the growth and clock phenotypes of CRISPR-Cas9-generated single, double, and triple rve mutants. We found that these genes act synergistically to regulate flowering time, redundantly to regulate leaf growth, and antagonistically to regulate hypocotyl elongation. We previously reported that increasing intensities of monochromatic blue and red light have opposite effects on the period of triple rve468 mutants. Here, we further examined light quality-specific phenotypes of rve mutants and report that rve468 mutants lack the blue light-specific increase in expression of some circadian clock genes observed in wild type. To investigate the basis of these blue light-specific circadian phenotypes, we examined RVE protein abundances and degradation rates in blue and red light and found no significant differences between these conditions. We next examined genetic interactions between RVE genes and ZEITLUPE and ELONGATED HYPOCOTYL5, two factors with blue light-specific functions in the clock. We found that the RVEs interact additively with both ZEITLUPE and ELONGATED HYPOCOTYL5 to regulate circadian period, which suggests that neither of these factors are required for the blue light-specific differences that we observed. Overall, our results suggest that the RVEs have separable functions in plant growth and circadian regulation and that they are involved in blue light-specific circadian signaling via a novel mechanism.

Applicability of a new method for mesoscopic structure segmentation of asphalt mixture based on two-dimensional image

The mechanical properties of the asphalt mixture largely depend on its internal structure. Studies in mixture mesostructure are of great significance for perfecting relevant theoretical systems and improving mixture design methods. However, efficient segmentation of mesostructure is an important precondition for mesoscale research about asphalt mixtures. Therefore, this article proposes a new method for mesostructure information acquisition that mainly improves the function of image preprocessing and separation of touching objects. A visual and quantitative comparison between the proposed and common methods is adopted. The result shows that the proposed method performs better in identifying small particles and retaining the fidelity of the boundary. Besides, the mesostructure of four types of asphalt mixtures are compared based on the proposed method. The result shows that the optimum sample size, which makes the measured 2D information efficiently close to the actual 3D information, is around 20–30. Compared to SUP25, the coordination number of AC20 is about 0.15–0.23 higher. Compared with the samples compacted by Marshall, the samples compacted by gyratory have a larger coordination number, about 0.12–0.21 higher, a larger fractal dimension, about 0.059–0.062 higher, a smaller uniformity of major axis orientation, about 1.53–1.28 lower, and a smaller uniformity of area distribution, about 0.063–0.12 lower.

Open Education and Alternative Digital Credentials in Europe

Learners who learn from OER often cannot have their learning assessed or receive a credential. Open credentials offer a potential solution to this problem, combining badges or micro-credentials with competence frameworks and digital seals. This study identified the current situation of open credentials in post-secondary education in Europe, the main themes of the discourse, and the points of agreement and divergence surrounding them. The data comprised a corpus of transcriptions from 12 expert interviews and a focus group. Qualitative text analysis identified the principal themes. Findings included the following: (a) few assessments are available as open content; (b) linking OER and credentials requires detailed and expensive work on learning outcomes and assessment; (c) the aggregation of open credentials to create higher-level qualifications is a widely accepted ambition; (d) the European Union’s infrastructure to support open credentials is appropriate and effective and can foster trust; (e) the outstanding challenges are organisational and practical, not technological; (f) assessment and content provisions should belong to separate organisational functions; and finally, (g) funding and support for open credentials in professional accreditation are essential for further progress.

An energy‐efficient tunable threshold spiking neuron with excitatory and inhibitory function

AbstractIn this work, a complementary metal‐oxide‐semiconductor (CMOS) based leaky‐integrate and fire neuron has been proposed and investigated for neuromorphic applications. The neuron has been designed in Cadence Virtuoso and validated experimentally. It has been observed that the neuron consumes a maximum energy of 68.87 fJ/spike. The response of the neuron to excitatory as well as inhibitory inputs has been studied. To verify the applicability, the proposed neuron has been explored for reconfigurable threshold logic to implement various linearly separable Boolean functions including OR, AND, NOT, NOR, and NAND. Moreover, the threshold tunability of the neuron has also been verified and this property has been exploited to design threshold‐controlled logic gates. Instead of adjusting the weights of the applied inputs, the functionality of such gates can be controlled by changing the threshold of the neuron, simplifying the synaptic architecture of a neural network. Finally, a multilayer network has been designed and the recognition ability of the proposed network for MNIST handwritten digits has been verified with an accuracy of 96.93%.

Preferred Oral Corrective Feedback through Existing Internalized Language Prejudice of Students in the Philippines

Following the 2022 Program for International Student Assessment (PISA) test results, it was found out that the Philippines ranked 76th in reading comprehension among 81 PISA-participating countries. Students from the Philippines are still among the least proficient in the world in reading comprehension. With the country performing below the standards and criterion set by the organization, the researchers investigate internalized language prejudice as learners’ primary obstruction in acquiring the English language. Provided that the Oral Corrective Feedback (OCF) is essential for students’ learning process and performing separate functions in acquiring the English language, this paper aims to figure out their preferred OCF in acquiring the language. Furthermore, the proponents of the study delve into the reasons of the selected students when given an OCF in connection and relevance with how internalized language prejudice, stereotypes, and preconceived notions come into play in terms of the effectiveness of the English language learning and teaching. Lastly, the paper used mixed methods in gathering data: quantitative through an online survey form and qualitative through Focus Group Discussions (FGD).

Interacting galaxies in the IllustrisTNG simulations – VI: Reconstructed orbits, close encounters, and mergers

ABSTRACT Cosmological simulations have been used to study interacting galaxies as a function of galaxy pair separation, enabling comparisons with observational studies of galaxy pairs. The study of interacting galaxies as a function of time (i.e. merger stage) has mostly been limited to high-resolution merger simulations, due to the poor time sampling available in cosmological simulations. Building on an earlier study of galaxy pairs in the IllustrisTNG cosmological simulations, we reconstruct the orbits of galaxy pairs involving massive galaxies (M* > 1010 M⊙) at redshifts of 0 ≤ z < 1, using a novel kinematic interpolation scheme to model the orbits in between the IllustrisTNG snapshots (which are separated by 162 Myr, on average). We assess the accuracy of these interpolations using a pre-existing suite of merger simulations, and find that kinematic interpolations provide a remarkable improvement in accuracy compared with interpolations that use only radial separations or 3D positions. We find that nearly 90 per cent of the closest pairs (r < 25 kpc) have had a pericentre encounter within the past Gyr. Many of these close pairs are found on rapidly shrinking orbits, and roughly 85 per cent of these pairs will merge within 1 Gyr. However, approximately 3 per cent of these close pairs appear to be flyby systems that will never merge. These reconstructed orbits will be used in future studies to investigate how and when galaxy properties change during close encounters and mergers between galaxies in IllustrisTNG.

Many-body theory calculations of positronic-bonded molecular dianions.

The energetic stability of positron-dianion systems [A-;e+; A-] is studied via many-body theory, where A- includes H-, F-, Cl-, and the molecular anions (CN)- and (NCO)-. Specifically, the energy of the system as a function of ionic separation is determined by solving the Dyson equation for the positron in the field of the two anions using a positron-anion self-energy as constructed in Hofierka et al. [Nature 606, 688 (2022)] that accounts for correlations, including polarization, screening, and virtual-positronium formation. Calculations are performed for a positron interacting with H22-, F22-, and Cl22- and are found to be in good agreement with previous theory. In particular, we confirm the presence of two minima in the potential energy of the [H-;e+; H-] system with respect to ionic separation: a positronically bonded [H-;e+; H-] local minimum at ionic separations r ∼ 3.4 Å and a global minimum at smaller ionic separations r ≲ 1.6 Å that gives overall instability of the system with respect to dissociation into a H2 molecule and a positronium negative ion, Ps-. The first predictions are made for positronic bonding in dianions consisting of molecular anionic fragments, specifically for (CN)22- and (NCO)22-. In all cases, we find that the molecules formed by the creation of a positronic bond are stable relative to dissociation into A- and e+A- (positron bound to a single anion), with bond energies on the order of 1eV and bond lengths on the order of several ångstroms.

Magnetic interactions in vortex-state nanodisk arrays characterized by gradient magnetic vortex echo

Magnetic vortices have potential applications in the field of spintronics and medicine and studying their magnetic interactions is crucial for future applications. This work introduces a new method based on obtaining the gradient magnetic vortex echo (GMVE) using micromagnetic simulations following a magnetic resonance imaging protocol. The results show that it is possible to characterize the magnetic interaction of arrays of nanodisks, having equal diameter and vortex configuration, as a function of disk separation. This characterization was performed by creating an inhomogeneity in the system through the application of a magnetic field gradient perpendicular to the plane of the nanodisk array. The inhomogeneity allows refocusing the magnetization in a time-controlled way by inverting the sign of the gradient and obtaining the characteristic transverse relaxation time T2∗ from the GMVE that contains the information on the magnetic interaction.

Separating the effects of life course adiposity on diabetic nephropathy: a comprehensive multivariable Mendelian randomization study.

Previous Mendelian randomization (MR) of obesity and diabetic nephropathy (DN) risk used small sample sizes or focused on a single adiposity metric. We explored the independent causal connection between obesity-related factors and DN risk using the most extensive GWAS summary data available, considering the distribution of adiposity across childhood and adulthood. To evaluate the overall effect of each obesity-related exposure on DN (Ncase = 3,676, Ncontrol = 283,456), a two-sample univariate MR (UVMR) analysis was performed. The independent causal influence of each obesity-related feature on DN was estimated using multivariable MR (MVMR) when accounting for confounding variables. It was also used to examine the independent effects of adult and pediatric obesity, adjusting for their interrelationships. We used data from genome-wide association studies, including overall general (body mass index, BMI) and abdominal obesity (waist-to-hip ratio with and without adjustment for BMI, i.e., WHR and WHRadjBMI), along with childhood obesity (childhood BMI). UVMR revealed a significant association between adult BMI (OR=1.24, 95%CI=1.03-1.49, P=2.06×10-2) and pediatric BMI (OR=1.97, 95%CI=1.59-2.45, P=8.55×10-10) with DN risk. At the same time, adult WHR showed a marginally significant increase in DN (OR =1.27, 95%CI = 1.01-1.60, P=3.80×10-2). However, the outcomes were adverse when the influence of BMI was taken out of the WHR (WHRadjBMI). After adjusting for childhood BMI, the causal effects of adult BMI and adult abdominal obesity (WHR) on DN were significantly attenuated and became nonsignificant in MVMR models. In contrast, childhood BMI had a constant and robust independent effect on DN risk(adjusted for adult BMI: IVW, OR=1.90, 95% CI=1.60-2.25, P=2.03×10-13; LASSO, OR=1.91, 95% CI=1.65-2.21, P=3.80×10-18; adjusted for adult WHR: IVW, OR=1.80, 95% CI=1.40-2.31, P=4.20×10-6; LASSO, OR=1.90, 95% CI=1.56-2.32, P=2.76×10-10). Our comprehensive analysis illustrated the hazard effect of obesity-related exposures for DN. In addition, we showed that childhood obesity plays a separate function in influencing the risk of DN and that the adverse effects of adult obesity (adult BMI and adult WHR) can be substantially attributed to it. Thus, several obesity-related traits deserve more attention and may become a new target for the prevention and treatment of DN and warrant further clinical investigation, especially in childhood obesity.

Amplitude methods for forming frequency-independent radiation characteristics of multibeam reflector antennas

The trend towards expanding the operating frequency ranges of radio-electronic equipment has led to an increasing interest in recent years in the study of ways to constructing multi-beam frequency-independent reflector antennas, which requires systematization of the principles and methods of their construction. When constructing reflector antennas, methods based on the selection of the directional properties of the feeds and methods based on the selection of the frequency-selective properties of the reflectors are used. Methods based on the choice of directional properties of feeds are divided into methods using horn feeds and methods using feeds in the form of cluster arrays with intersecting apertures. Horn feeds are used to create single-beam reflector antennas. Using cluster arrays, it is possible to form a plurality of beams of frequency-independent partial radiation patterns. Using the example of a hybrid reflector antenna, the possibility of forming nine beams in the azimuthal sector of 20° with a beam width of 3.2° ± 0.45° in the frequency band from 2 to 8 GHz is shown. The level of side lobes outside the working sector in the operating frequency band does not exceed –35 dB, the slope of the direction-finding characteristics varies from 4.8 to 9.8 dB/deg. Among the methods based on the choice of selective properties of reflectors, there are methods using frequency-selective surfaces and methods using corrective coatings on the working surface of the reflector. Frequency-selective surfaces are made in the form of wire meshes with variable pitch, in the form of a set of parabolic plates and in the form of a set of square waveguides with a side size ranging from half-wave at the upper frequency in the middle part of the reflector to half-wave at the lower operating frequency at the edges of the reflector. The disadvantages of using frequency-selective surfaces are the complex and expensive design of the reflector, low antenna efficiency, high side lobes and the need to use a large absorbing screen. When implementing the method using corrective coatings, the separate functions of a frequency-selective surface and a radio-absorbing screen are combined in one structural element – a frequency-dependent corrective coating applied to the working surface of the reflector. Among the advantages of this method, it is worth noting the simple design of the reflector and the possibility of its operation at any polarization, since the reflection characteristics of the coating are practically independent of the type of polarization. A common disadvantage of reflector antennas based on the choice of frequency-selective properties of reflectors is distortion of the shape of the main lobe of partial patterns and a larger range of scatter in the pattern width in the operating frequency band, which prevents the formation of linear direction-finding characteristics and reduces direction-finding accuracy. Due to the low efficiency of multibeam mirror antennas built using amplitude methods for forming frequency-independent radiation characteristics, their use as transmitting antennas is impractical. The completed review and identified features of methods for constructing frequency-independent radiation characteristics can become a methodological basis for the design of broadband multi-beam reflector antenna systems for advanced radio-electronic equipment.

Dynamical Friction Models for Black Hole Binary Formation in Active Galactic Nucleus Disks

Stellar-mass black holes (sBHs) embedded in gaseous disks of active galactic nuclei (AGN) can be important sources of detectable gravitational radiation for LIGO/Virgo when they form binaries and coalesce due to orbital decay. In this paper, we study the effect of dynamical friction (DF) on the formation of BH binaries in AGN disks using N-body simulations. We employ two simplified models of DF, with the force on the BH depending on Δ v , the velocity of the sBH relative to the background Keplerian gas. We integrate the motion of two sBHs initially on circular orbits around the central supermassive black hole (SMBH) and evaluate the probability of binary formation under various conditions. We find that both models of DF (with different dependence of the frictional coefficient on ∣Δ v ∣) can foster the formation of binaries when the effective friction timescale τ satisfies ΩK τ ≲ 20–30 (where ΩK is the Keplerian frequency around the SMBH): prograde binaries are formed when the DF is stronger (smaller τ), while retrograde binaries dominate when the DF is weaker (larger τ). We determine the distribution of both prograde and retrograde binaries as a function of initial orbital separation and the DF strength. Using our models of DF, we show that for a given sBH number density in the AGN disk, the formation rate of sBH binaries increases with decreasing τ and can reach a moderate value with a sufficiently strong DF.

Chemical Methods to Identify Epigenetic Modifications in Cytosine Bases.

Chemical modifications to Cytosine bases are among the most studied epigenetic markers and their detection in the human genome plays a crucial role in gaining more insights about gene regulation, prognosis of genetic disorders and unraveling genetic inheritance patterns. The Cytosine methylated at the 5th position and oxidized derivatives thereof generated in the demethylation pathways, perform separate and unique epigenetic functions in an organism. As the presence of various Cytosine modifications is associated with diverse diseases, including cancer, there has been a strong focus on developing methods, both chemical and alternative approaches, capable of detecting these modifications at a single-base resolution across the entire genome. In this comprehensive review, we aim to consolidate the various chemical methods and understanding their chemistry that have been established to date for the detection of various Cytosine modifications.

An improved indirect adaptive neural control performance based on MOPSO approach: An experimental validation via a transesterification reactor

This paper proposes an indirect adaptive control method based on recurrent neural networks. To achieve satisfactory closed-loop performances, a neural emulator (NE) and a neural controller (NC) adapting rates are established using the multiobjective particle swarm optimization (MOPSO) algorithm. The proposed MOPSO algorithm has been designed to minimize, simultaneously, two separated objective functions: the emulation and the tracking errors. The proposed approach guarantees that the NE tracks the system dynamics within a short time window. Consequently, it provides for the suggested control structure useful information to synthesize optimal adaptive rates of the NE and NC. To validate the effectiveness of the proposed MOPSO algorithm, a numerical example and an experimental validation on a chemical reactor are proposed.

On the pythagorean structure of the optimal transport for separable cost functions

In this paper, we study the optimal transport problem induced by two measures supported over two polish spaces, namely, X and Y , which are the product of n smaller polish spaces, that is, X={\Large{\times}}_{j=1}^n X_j and Y={\Large{\times}}_{j=1}^n Y_j . In particular, we focus on problems induced by a cost function c:X\times Y\to [0,+\infty) that is separable; i.e., c is such that c=c_1+\dots+c_n , where each c_j depends only on the couple (x_j,y_j) , and thus c_j:X_j\times Y_j\to [0,+\infty) . Noticeably, if X=Y=\mathbb{R}^n , this class of cost functions includes all the l_p^p costs. Our main result proves that the optimal transportation plan with respect to a separable cost function between two given measures can be expressed as the composition of n different lower-dimensional transports, one for each pair of coordinates (x_i,y_i) in X\times Y . This allows us to decompose the entire Wasserstein cost as the sum of n lower-dimensional Wasserstein costs and to prove that there always exists an optimal transportation plan whose random variable enjoys a conditional independence property with respect to its marginals. We then show that our formalism allows us to explicitly compute the optimal transportation plan between two probability measures when each measure has independent marginals. Finally, we focus on two specific frameworks. In the first one, the cost function is a separable distance, i.e., d=d_1+d_2 , where both d_1 and d_2 are distances themselves. In the second one, both measures are supported over \mathbb{R}^n and the cost function is of the form c(x,y)=h(\vert x_1-y_1\vert)+h(\vert x_2-y_2\vert) , where h is a convex function such that h(0)=0 .

Abstract B115: Single-cell transcriptomic analysis reveals both shared and separate functions for GATA6 and KRT17 in pancreatic cancer

Abstract Human pancreatic ductal carcinomas (PDACs) are transcriptionally heterogeneous and can be grouped into two classes, the classical subtype associated with GATA6 expression and the basal subtype associated with KRT17 expression. Accordingly, GATA6 and KRT17 are generally thought to have opposing functions in PDAC. However, through our analysis of single cell RNA sequencing data, we have found that many of the genes that are the highly correlated with KRT17 expression are also highly correlated with GATA6 expression, including KLF5, which encodes a transcription factor that promotes PDAC development, and several genes that encode components of intercellular junctions (e.g. CDH1, CLDN4, CLDN18, JUP, and SHROOM3). These results suggest that KRT17 and GATA6 share certain biological functions including the maintenance or modulation of intercellular junctions. We also found evidence for separate functions. Genes with expression that correlated specifically with GATA6 included transcription factor genes involved in normal pancreatic differentiation along with genes encoding components of the Hippo signaling pathway. On the other hand, genes with expression that correlated specifically with KRT17 included several components of PIK3-Akt signaling. Further analysis of scRNA-seq data should reveal more about the mechanisms by which these genes are involved in influencing PDAC progression and maintenance. Citation Format: Brian J. Nelson, Natalie Marchenko, Luisa F. Escobar-Hoyos, Kenneth Shroyer, Scott Powers, Thomas MacCarthy. Single-cell transcriptomic analysis reveals both shared and separate functions for GATA6 and KRT17 in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr B115.