Canonical Properties Research Articles

Hepatic FGF21: Its Emerging Role in Inter-Organ Crosstalk and Cancers.

Fibroblast growth factor (FGF) 21 is one of the FGF members with special endocrine properties. In the last twenty years, it has attracted intense research and development for its physiological functions that respond to dietary manipulation, pharmacological benefits of improving the macronutrient metabolism, and clinical values as a biomarker of various human diseases. Generally, FGF21 can be produced by major metabolic organs, but only the subgroup from the liver shows canonical endocrine properties, which emphasizes the special value of delineating the unique secretory and functional characteristics of hepatic FGF21. There has been a growth in literature to address the extra-hepatic activities of FGF21, and many striking findings have therefore been published. Yet, they are fragmented and scattered, and controversies are raised from divergent findings. For this reason, there is a need for a systematic and critical evaluation of current research in this aspect. In this review, we focus on the current knowledge about the molecular biology of endocrine FGF21, especially present details on the regulation of circulating levels of FGF21. We also emphasize its emerging roles in inter-organ crosstalk and cancer development.

A pragmática dos dogwhistles algumas questões

Dogwhistles are communicative mechanisms for expressing subliminal meanings. In this paper, I take up the distinction, usual in the literature on the topic, between two types of dogwhistle: overt and covert, whereby in the latter, as opposed to the former, the preservation of the subliminal character of the message seems to be a necessary condition for the dogwhistle’s communicative success. I discuss various aspects of this distinction, arguing that both types of dogwhistle can be analysed as conversational implicatures bearing in mind, in particular, the canonical properties of cancelability and calculability.

NF-κB Rel subunit exchange on a physiological timescale.

The Rel proteins of the NF-κB complex comprise one of the most investigated transcription factor families, forming a variety of hetero- or homodimers. Nevertheless, very little is known about the fundamental kinetics of NF-κB complex assembly, or the inter-conversion potential of dimerised Rel subunits. Here, we examined an unexplored aspect of NF-κB dynamics, focusing on the dissociation and reassociation of the canonical p50 and p65 Rel subunits and their ability to form new hetero- or homodimers. We employed a soluble expression system to enable the facile production of NF-κB Rel subunits, and verified these proteins display canonical NF-κB nucleic acid binding properties. Using a combination of biophysical techniques, we demonstrated that, at physiological temperatures, homodimeric Rel complexes routinely exchange subunits with a half-life of less than 10min. In contrast, we found a dramatic preference for the formation of the p50/p65 heterodimer, which demonstrated a kinetic stability of at least an order of magnitude greater than either homodimer. These results suggest that specific DNA targets of either the p50 or p65 homodimers can only be targeted when these subunits are expressed exclusively, or with the intervention of additional post-translational modifications. Together, this work implies a new model of how cells can modulate NF-κB activity by fine-tuning the relative proportions of the p50 and p65 proteins, as well as their time of expression. This work thus provides a new quantitative interpretation of Rel dimer distribution in the cell, particularly for those who are developing mathematical models of NF-κB activity.

PROKR1 delivery by cell-derived vesicles restores the myogenic potential of Prokr1-deficient C2C12 myoblasts

Cell-derived vesicles (CDVs) have been investigated as an alternative to exosomes. Here, we generated CDVs from Prokineticin receptor 1 (PROKR1) overexpressing HEK293T cells using micro-extrusion. More than 60 billion PROKR1-enriched CDV (PROKR1Tg CDVs) particles with canonical exosome properties were recovered from 107 cells. With 25 μg/mL of PROKR1Tg CDVs, we observed delivery of PROKR1, significant reduction of apoptosis, and myotube formation in C2C12Prokr1−/− myoblasts that have lost their myogenic potential but underwent apoptosis following myogenic commitment. Expression levels of early and late myogenic marker genes and glucose uptake capacity were restored to equivalent levels with wild-type control. Furthermore, PROKR1Tg CDVs were accumulated in soleus muscle comparable to the liver without significant differences. Therefore, CDVs obtained from genetically engineered cells appear to be an effective method of PROKR1 protein delivery and offer promise as an alternative therapy for muscular dystrophy.

Algorithms for Quantum Simulation at Finite Energies

We introduce two kinds of quantum algorithms to explore microcanonical and canonical properties of many-body systems. The first one is a hybrid quantum algorithm that, given an efficiently preparable state, computes expectation values in a finite energy interval around its mean energy. This algorithm is based on a filtering operator, similar to quantum phase estimation, which projects out energies outside the desired energy interval. However, instead of performing this operation on a physical state, it recovers the physical values by performing interferometric measurements without the need to prepare the filtered state. We show that the computational time scales polynomially with the number of qubits, the inverse of the prescribed variance, and the inverse error. In practice, the algorithm does not require the evolution for long times, but instead a significant number of measurements in order to obtain sensible results. Our second algorithm is a quantum-assisted Monte Carlo sampling method to compute other quantities which approach the expectation values for the microcanonical and canonical ensembles. Using classical Monte Carlo techniques and the quantum computer as a resource, this method circumvents the sign problem that is plaguing classical Quantum Monte Carlo simulations, as long as one can prepare states with suitable energies. All algorithms can be used with small quantum computers and analog quantum simulators, as long as they can perform the interferometric measurements. We also show that this last task can be greatly simplified at the expense of performing more measurements.

Gauge invariant canonical symplectic algorithms for real-time lattice strong-field quantum electrodynamics

A class of high-order canonical symplectic structure-preserving geometric algorithms are developed for high-quality simulations of the quantized Dirac-Maxwell theory based strong-field quantum electrodynamics (SFQED) and relativistic quantum plasmas (RQP) phenomena. With minimal coupling, the Lagrangian density of an interacting bispinor-gauge fields theory is constructed in a conjugate real fields form. The canonical symplectic form and canonical equations of this field theory are obtained by the general Hamilton’s principle on cotangent bundle. Based on discrete exterior calculus, the gauge field components are discreted to form a cochain complex, and the bispinor components are naturally discreted on a staggered dual lattice as combinations of differential forms. With pull-back and push-forward gauge covariant derivatives, the discrete action is gauge invariant. A well-defined discrete canonical Poisson bracket generates a semi-discrete lattice canonical field theory (LCFT), which admits the canonical symplectic form, unitary property, gauge symmetry and discrete Poincaré subgroup, which are good approximations of the original continuous geometric structures. The Hamiltonian splitting method, Cayley transformation and symmetric composition technique are introduced to construct a class of high-order numerical schemes for the semi-discrete LCFT. These schemes involve two degenerate fermion flavors and are locally unconditional stable, which also preserve the geometric structures. Admitting Nielsen-Ninomiya theorem, the continuous chiral symmetry is partially broken on the lattice. As an extension, a pair of discrete chiral operators are introduced to reconstruct the lattice chirality. Equipped with statistically quantization-equivalent ensemble models of the Dirac vacuum and non-trivial plasma backgrounds, the schemes are expected to have excellent performance in secular simulations of relativistic quantum effects, where the numerical errors of conserved quantities are well bounded by very small values without coherent accumulation. The algorithms are verified in detail by numerical energy spectra. Real-time LCFT simulations are successfully implemented for the nonlinear Schwinger mechanism induced e-e+ pairs creation and vacuum Kerr effect, where the nonlinear and non-perturbative features captured by the solutions provide a complete strong-field physical picture in a very wide range, which open a new door toward high-quality simulations in SFQED and RQP fields.

On a linear autonomous descriptor equation with discrete time. II. Canonical representation and structural properties

We consider a linear homogeneous autonomous descriptor equation with discrete time B0g(k+1)+∑mi=1Big(k+1−i)=0,k=m,m+1,…, with rectangular (in general case) matrices Bi. Such an equation arises in the study of the most important control problems for systems with many commensurate delays in control: the 0-controllability problem, the synthesis problem of the feedback-type regulator, which provides calming to the solution of the original system, the modal controllability problem (controllability to the coefficients of characteristic quasipolynomial), the spectral reduction problem and the synthesis problem observers for dual surveillance system. The main method of the presented study is based on replacing the original equation with an equivalent equation in the “expanded” state space, which allows one to match the new equation of the beam of matrices. This made it possible to study a number of structural properties of the original equation by using the canonical form of the beam of matrices, and express the results in terms of minimal indices and elementary divisors. In the article, a criterion is obtained for the existence of a nontrivial admissible initial condition for the original equation, the verification of which is based on the calculation of the minimum indices and elementary divisors of the beam of matrices. The following problem was studied: it is required to construct a solution to the original equation in the form g(k+1)=Tψ(k+1), k=1,2…, where T is some matrix, the sequence of vectors ψ(k+1), k=1,2,…, satisfies the equation ψ(k+1)=Sψ(k), k=1,2,…, and the square matrix S has a predetermined spectrum (or part of the spectrum). The results obtained make it possible to construct solutions of the initial descriptor equation with predetermined asymptotic properties, for example, uniformly asymptotically stable.

Structural analysis of the sensor domain of the β-lactam antibiotic receptor VbrK from Vibrio parahaemolyticus

Bacteria express β-lactamase to counteract the bactericidal effects of β-lactam antibiotics, which are the most widely employed antibacterial drugs. In gram-negative bacteria, the expression of β-lactamase is generally regulated in response to the muropeptide that is generated from the peptidoglycan of the cell wall during β-lactam antibiotic challenge. The direct regulation of β-lactamase expression by β-lactams was recently reported in Vibrio parahaemolyticus, and this regulation is mediated by a two-component regulatory system that consists of the histidine kinase VbrK and the response regulator VbrR. VbrK directly recognizes β-lactam antibiotics using the periplasmic sensor domain (VbrKSD), a PF11884 Pfam family member, and it delivers the β-lactam signal to VbrR to induce the transcription of the β-lactamase gene. To determine the structural features of VbrKSD as the prototype of the PF11884 family and provide insights into the β-lactam antibiotic-binding mode of VbrKSD, we determined the crystal structure of VbrKSD at 1.65 Å resolution. VbrKSD folds into a unique curved rod-like structure that has not been previously reported in other families. VbrKSD consists of two domains (D1 and D2). The D1 domain contains two helix-decorated β-sheets, and the D2 domain adopts a helix-rich structure. VbrKSD features two terminal disulfide bonds, which would be the canonical property of the PF11884 family. In the VbrKSD structure, the L82 residue, which was previously shown to play a key role in β-lactam antibiotic recognition, forms a pocket along with its neighboring hydrophobic or positively charged residues.

Expanding Canonical Spider Silk Properties through a DNA Combinatorial Approach.

The properties of native spider silk vary within and across species due to the presence of different genes containing conserved repetitive core domains encoding a variety of silk proteins. Previous studies seeking to understand the function and material properties of these domains focused primarily on the analysis of dragline silk proteins, MaSp1 and MaSp2. Our work seeks to broaden the mechanical properties of silk-based biomaterials by establishing two libraries containing genes from the repetitive core region of the native Latrodectus hesperus silk genome (Library A: genes masp1, masp2, tusp1, acsp1; Library B: genes acsp1, pysp1, misp1, flag). The expressed and purified proteins were analyzed through Fourier Transform Infrared Spectrometry (FTIR). Some of these new proteins revealed a higher portion of β-sheet content in recombinant proteins produced from gene constructs containing a combination of masp1/masp2 and acsp1/tusp1 genes than recombinant proteins which consisted solely of dragline silk genes (Library A). A higher portion of β-turn and random coil content was identified in recombinant proteins from pysp1 and flag genes (Library B). Mechanical characterization of selected proteins purified from Library A and Library B formed into films was assessed by Atomic Force Microscopy (AFM) and suggested Library A recombinant proteins had higher elastic moduli when compared to Library B recombinant proteins. Both libraries had higher elastic moduli when compared to native spider silk proteins. The preliminary approach demonstrated here suggests that repetitive core regions of the aforementioned genes can be used as building blocks for new silk-based biomaterials with varying mechanical properties.

Non-canonical Receptive Field Properties and Neuromodulation of Feature-Detecting Neurons in Flies

Several fundamental aspects of motion vision circuitry are prevalent across flies and mice. Both taxa segregate ON and OFF signals. For any given spatial pattern, motion detectors in both taxa are tuned to speed, selective for one of four cardinal directions, and modulated by catecholamine neurotransmitters. These similarities represent conserved, canonical properties of the functional circuits and computational algorithms for motion vision. Less is known about feature detectors, including how receptive field properties differ from the motion pathway or whether they are under neuromodulatory control to impart functional plasticity for the detection of salient objects from a moving background. Here, we investigated 19 types of putative feature selective lobula columnar (LC) neurons in the optic lobe of the fruit fly Drosophila melanogaster to characterize divergent properties of feature selection. We identified LC12 and LC15 as feature detectors. LC15 encodes moving bars, whereas LC12 is selective for the motion of discrete objects, mostly independent of size. Neither is selective for contrast polarity, speed, or direction, highlighting key differences in the underlying algorithms for feature detection and motion vision. We show that the onset of background motion suppresses object responses by LC12 and LC15. Surprisingly, the application of octopamine, which is released during flight, reverses the suppressive influence of background motion, rendering both LCs able to track moving objects superimposed against background motion. Our results provide a comparative framework for the function and modulation of feature detectors and new insights into the underlying neuronal mechanisms involved in visual feature detection.

Abelian-Higgs cosmic string evolution with CUDA

Topological defects form at cosmological phase transitions by the Kibble mechanism, with cosmic strings—one-dimensional defects—being the most studied example. A rigorous analysis of their astrophysical consequences is limited by the availability of accurate numerical simulations, and therefore by hardware resources and computation time. Improving the speed and efficiency of existing codes is therefore important. All current cosmic string simulations were performed on Central Processing Units. In previous work we presented a General Purpose Graphics Processing Unit implementation of the evolution of cosmological domain wall networks. Here we discuss an analogous implementation for local Abelian-Higgs string networks. We discuss the implementation algorithm (including the discretisation used and how to calculate network averaged quantities) and then showcase its performance and current bottlenecks. We validate the code by directly comparing our results for the canonical scaling properties of the networks in the radiation and matter eras with those in the literature, finding very good agreement. We finally highlight possible directions for improving the scalability of the code.

Abstract A27: Deep learning for analysis of tumor-lymphocyte interactions in pancreatic ductal adenocarcinoma

Abstract The interaction of tumor, stroma, and immune cells in pancreatic ductal adenocarcinoma (PDAC) is complex and difficult to quantify in patient samples. Recently, deep learning algorithms have shown successes in identifying tumor and lymphocytes regions on whole-slide images derived from routinely collected histopathologic specimens. The Cancer Genome Atlas (TCGA) in particular has generated whole-slide images as well as paired molecular data, thus allowing for combined spatial and molecular analyses of tumor-lymphocyte interactions. We have previously highlighted this resource by computationally mapping tumor-infiltrating lymphocytes (TILs) on digital images across 13 tumor types. To achieve this, convolutional neural networks were trained on lymphocyte images annotated by expert pathologists and then used to detect spatial TIL patterns. This led to identification of four qualitative TIL pattern categories, which varied depending on tumor type as well as molecular immune subtype, demonstrating the potential of these spatial structures to provide further insights into tumor microenvironments and their relationship to overall survival. We have now extended this deep learning pipeline to include identification of tumor regions in PDAC, allowing study of TIL patterns in the context of their relative spatial localization to tumors. Using the deep learning algorithm to define the tumor region, we applied erosion and dilation operations to further capture the peritumoral region, the outer and inner regions of the tumor, as well as desmoplasia far from the tumor cells. We thus defined lymphocytes by their spatial localization as being internal, tumoral, peritumoral, or outer with these masks. We then used nearest-neighbor and density-based approaches to quantify TIL infiltration patterns with respect to tumor. These features vary significantly across the previously identified TIL patterns and may serve as additional parameters to define the microenvironment conditions in patient samples. Here we demonstrate that features extracted using our pipeline recapitulate canonical histologic properties. Using immune cell abundance estimates from gene expression generated by CIBERSORT, we find that samples with tumor TIL densities above median have more M1 macrophages, while those below median have more M2 macrophages. We also observe that slides with a higher peritumoral TIL density relative to tumoral TIL density have higher Treg fractions. Ongoing work on improving the resolution and cell specificity of our pipeline will allow us to ask more specific questions and permit higher granularity in linking clinical outcomes to spatial immune phenotypes. Citation Format: Soma Kobayashi, Han Le, Lucie Chrastecka, Rajarsi Gupta, Le Hou, Shahira Abousamra, Danielle Fassler, Kenneth R. Shroyer, Dimitris Samaras, Tahsin Kurc, Richard A. Moffitt, Joel H. Saltz. Deep learning for analysis of tumor-lymphocyte interactions in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr A27.

Overcoming Noise in Entanglement Distribution

Noise can be considered the natural enemy of quantum information. An often implied benefit of high-dimensional entanglement is its increased resilience to noise. However, manifesting this potential in an experimentally meaningful fashion is challenging and has never been done before. In infinite dimensional spaces, discretisation is inevitable and renders the effective dimension of quantum states a tunable parameter. Owing to advances in experimental techniques and theoretical tools, we demonstrate an increased resistance to noise by identifying two pathways to exploit high-dimensional entangled states. Our study is based on two separate experiments utilising canonical spatio-temporal properties of entangled photon pairs. Following these different pathways to noise resilience, we are able to certify entanglement in the photonic orbital-angular-momentum and energy-time degrees of freedom up to noise conditions corresponding to a noise fraction of 72 % and 92 % respectively. Our work paves the way towards practical quantum communication systems that are able to surpass current noise and distance limitations, while not compromising on potential device-independence.

Constraining X-Ray Coronal Size with Transverse Motion of AGN Ultra-fast Outflows

Abstract One of the canonical physical properties of ultra-fast outflows (UFOs) seen in a diverse population of active galactic nuclei is its seemingly very broad width (i.e., Δv ≳ 10,000 km s−1), a feature often required for X-ray spectral modeling. While unclear to date, this condition is occasionally interpreted and justified as internal turbulence within the UFOs for simplicity. In this work, we exploit a transverse motion of a three-dimensional accretion disk-wind, an essential feature of nonradial outflow morphology unique to magnetohydrodynamic outflows. We argue that at least part of the observed line width of UFOs may reflect the degree of transverse velocity gradient due to Doppler broadening around a putative compact X-ray corona in the proximity of a black hole. In this scenario, line broadening is sensitive to the geometrical size of the corona, R c . We calculate the broadening factor as a function of coronal radius R c and velocity smearing factor f sm at a given plasma position. We demonstrate, as a case study of the quasar, PDS 456, that the spectral analysis favors a compact coronal size of R c /R g ≲ 10 where R g is gravitational radius. Such a compact corona is long speculated from both an X-ray reverberation study and the lamppost model for disk emission also consistent with microlensing results. Combination of such a transverse broadening around a small corona can be a direct probe of a substantial rotational motion perhaps posing a serious challenge to radiation-driven wind viewpoint.

Non-equilibrium vortex annealing of structural disorder in the critical relaxation of diluted two-dimensional XY-model

The study of the effects of aging in the non-equilibrium critical relaxation of a two-dimensional XY-model with a non-equilibrium vortex annealing of structural disorder has been carried out. Two-time dynamic dependencies of the spin-spin and defect-defect autocorrelation functions CSS (t,tw) and CDD (t,tw) are obtained for the entire Berezinskii low-temperature phase T < TBKT(p), for a wide range of waiting times tw and spin concentrations p. Near the BKT phase transition point TBKT (p), the dynamic dependencies CDD(t,tw) become uniform with time. However, with a decrease in temperature in the low-temperature phase T < TBKT (p), this relaxation uniformity breaks down, and CDD(t,tw) does not exhibit canonical aging properties. The formation of a declining family of dynamical scaling curves is clearly observed at large observation times t – tw which may indicate the presence of an asymptotic scaling dependence of CDD (t, tw).

Homomeric GluA2(R) AMPA receptors can conduct when desensitized

Desensitization is a canonical property of ligand-gated ion channels, causing progressive current decline in the continued presence of agonist. AMPA-type glutamate receptors (AMPARs), which mediate fast excitatory signaling throughout the brain, exhibit profound desensitization. Recent cryo-EM studies of AMPAR assemblies show their ion channels to be closed in the desensitized state. Here we present evidence that homomeric Q/R-edited AMPARs still allow ions to flow when the receptors are desensitized. GluA2(R) expressed alone, or with auxiliary subunits (γ-2, γ-8 or GSG1L), generates large fractional steady-state currents and anomalous current-variance relationships. Our results from fluctuation analysis, single-channel recording, and kinetic modeling, suggest that the steady-state current is mediated predominantly by conducting desensitized receptors. When combined with crystallography this unique functional readout of a hitherto silent state enabled us to examine cross-linked cysteine mutants to probe the conformation of the desensitized ligand binding domain of functioning AMPAR complexes.

Adaptation in models of visual object recognition

Convolutional neural network (CNN) models of the ventral stream provide an unprecedented opportunity to relate neural mechanisms to sensory representations and even perception. Current CNNs lack the temporal dynamics of biological vision such as adaptation to previous stimulation. Perceptually, adaptation has been widely studied in the form of aftereffects (Webster, 2015), while in single neurons adaptation is often equated to repetition suppression (Vogels, 2016). Whereas the two are often thought to be associated, they remain to be integrated in a truly general framework. One proposed mechanism underlying repetition suppression is a reduced excitability depending on previous neural activity, called response fatigue. Here, we implemented fatigue in each unit of a CNN (Krizhevsky et al., 2012) and asked whether it could account for more complex phenomena of neural and visual adaptation. Specifically, we assigned a latent fatigue variable to each unit that increased after high, but decreased after lower activation. The activation of a unit was then obtained by subtracting its fatigue from its input activity (before the linear rectifier). The resulting CNN units showed repetition suppression matching neural adaptation on several hallmark properties: stimulus-specificity, increased adaptation in higher layers, adaptation degree proportional with the number of repetitions (Vinken et al., 2017), and decreased adaptation with longer interstimulus intervals (Sawamura et al., 2006). Furthermore, the response patterns could account for the perceptual effects we tested: from afterimages in the first layer to a face gender aftereffect in later layers (Webster et al., 2004). Thus, when considered in a CNN, a simple mechanism of response fatigue operating at the level of single neurons can account for complex adaptation effects. In addition to providing a general model for adaptation, these results demonstrate the strength of using deep neural networks to connect low-level canonical neural properties or computations to high-level neural and perceptual phenomena.

Quantum correlations in periodically driven spin chains: Revivals and steady-state properties

Abstract We study the dynamics of microscopic quantum correlations, viz., bipartite entanglement and quantum discord between nearest neighbor sites, in Ising spin chain with a periodically varying external magnetic field along the transverse direction. Quantum correlations exhibit periodic revivals with the driving cycles in the finite-size chain. The time of first revival is proportional to the system size and is inversely proportional to the maximum group velocity of Floquet quasi-particles. On the other hand, the local quantum correlations in the infinite chain may get saturated to non-zero values after a sufficiently large number of driving cycles. Moreover, we investigate the convergence of local density matrices, from which the quantum correlations under study originate, towards the final steady-state density matrices as a function of driving cycles. We find that the geometric distance, d, between the reduced density matrices of non-equilibrium state and steady-state obeys a power-law scaling of the form d ∼ n - B , where n is the number of driving cycles and B is the scaling exponent. The steady-state quantum correlations are studied as a function of time period of the driving field and are marked by the presence of prominent peaks in frequency domain. The steady-state features can be further understood by probing band structures of Floquet Hamiltonian and purity of the bipartite state between nearest neighbor sites. Finally, we compare the steady-state values of the local quantum correlations with that of the canonical Gibbs ensemble and infer about their canonical ergodic properties. Moreover, we identify generic features in the ergodic properties depending upon the quantum phases of the initial state and the pathway of repeated driving that may be within the same quantum phase or across two different equilibrium phases.

Comparison of saddle point and exact combinatorial level densities

Accurate level densities are an important ingredient in the calculation of compound nucleus emission cross sections. They are often approximated numerically using the saddle point approximation to the canonical level density obtained from the grand canonical partition function using the inverse Laplace transform. Here, we use a modified version of the saddle-point approximation proposed by Rossignoli to obtain canonical level densities and average properties of a system. However, the level density needed in nuclear reaction calculations is actually the energy-conserving microcanonical one. For simple systems, the latter can be calculated combinatorially. Here we calculate microcanonical level densities using an evenly-spaced single particle density for one type of nucleon and compare these to saddle-point canonical level densities obtained from the same single-particle density. The simplest continuous approximation to the microcanonical level density describes it well near its peak but poorly at low excitation energies. The canonical level density obtained from the partition function fares somewhat better but is still not completely successful. It tends to exceed the exact result by a few percent. We discuss the differences between the canonical and microcanonical level densities and suggest how these might be reduced.

A juxtacrine/paracrine loop between C-Kit and stem cell factor promotes cancer stem cell survival in epithelial ovarian cancer

Receptors tyrosine kinase (RTK) enable normal and tumor cells to perceive and adapt to stimuli present in the microenvironment. These stimuli, also known as growth factors, are important molecular cues actively supporting cancer stem cell (CSC) self-renewal and viability. Since in epithelial ovarian cancer (EOC) the expression of c-Kit (CD117) has been identified as a CSC hallmark, we investigated the existence of a tumor growth-promoting loop between c-Kit and its ligand Stem Cell Factor (SCF). SCF exists as a soluble or transmembrane protein and through c-Kit interaction regulates cell viability, proliferation, and differentiation both in physiological and pathological conditions. High amounts of SCF were found in the ascitic effusions collected from EOC patients. While tumor cells and CSC only expressed the membrane-associated SCF isoform, both secreted and membrane-bound isoforms were expressed by tumor-associated macrophages (TAM, here shown to be M2-like) and fibroblasts (TAF). Circulating monocytes from EOC-bearing patients and healthy donors did not express both SCF isoforms. However, monocytes isolated from healthy donors produced SCF upon in vitro differentiation into macrophages, irrespectively of M1 or M2 polarization. In vitro, both SCF isoforms were able to activate the Akt pathway in c-Kit+ cells, and this effect was counteracted by the tyrosine kinase inhibitor imatinib. In addition, our results indicated that SCF could help c-Kit+ CSC survival in selective culture conditions and promote their canonical stemness properties, thus indicating the possible existence of a juxtacrine/paracrine circuit in EOC.