Embryo-uterine interaction coordinates mouse embryogenesis during implantation.

Embryo implantation into the uterus marks a key transition in mammalian development. In mice, implantation is mediated by the trophoblast and is accompanied by a morphological transition from the blastocyst to the egg cylinder. However, the roles of trophoblast-uterine interactions in embryo morphogenesis during implantation are poorly understood due to inaccessibility in utero and the remaining challenges to recapitulate it ex vivo from the blastocyst. Here, we engineer a uterus-like microenvironment to recapitulate peri-implantation development of the whole mouse embryo ex vivo and reveal essential roles of the physical embryo-uterine interaction. We demonstrate that adhesion between the trophoblast and the uterine matrix is required for in utero-like transition of the blastocyst to the egg cylinder. Modeling the implanting embryo as a wetting droplet links embryo shape dynamics to the underlying changes in trophoblast adhesion and suggests that the adhesion-mediated tension release facilitates egg cylinder formation. Light-sheet live imaging and the experimental control of the engineered uterine geometry and trophoblast velocity uncovers the coordination between trophoblast motility and embryo growth, where the trophoblast delineates space for embryo morphogenesis.

Phase Transitions and Nonlinear Optical Property Modifications in BaGa4Se7.

Phase transitions can change the crystal structure and modify the physical properties of crystals. In this work, we investigate the phase transition behavior in BaGa4Se7, an important middle infrared (mid-IR) nonlinear optical (NLO) crystal, in the temperature range from room temperature to 1173 K. Interestingly, the BaGa4Se7 crystal undergoes a reversible ferroelastic phase transition at T = 528 K, resulting in the presence of a newly discovered phase (γ-phase) at the higher temperature. The experimental temperature dependence of optical birefringence, as well as the first-principles birefringence and NLO coefficients, reveals that the γ-phase exhibits larger birefringence and better NLO properties compared with those of the low-temperature phase (α-phase). This work demonstrates that phase-transition-induced structural modification can improve the mid-IR NLO properties, which would provide an effective avenue to obtain materials with good optoelectronic performance.

Phospholipids dock SARS-CoV-2 spike protein via hydrophobic interactions: a minimal in-silico study of lecithin nasal spray therapy.

Understanding the physical and chemical properties of viral infections at molecular scales is a major challenge for the scientific community more so with the outbreak of global pandemics. There is currently a lot of effort being placed in identifying molecules that could act as putative drugs or blockers of viral molecules. In this work, we computationally explore the importance in antiviral activity of a less studied class of molecules, namely surfactants. We employ all-atoms molecular dynamics simulations to study the interaction between the receptor-binding domain of the SARS-CoV-2 spike protein and the phospholipid lecithin (POPC), in water. Our microsecond simulations show a preferential binding of lecithin to the receptor-binding motif of SARS-CoV-2 with binding free energies significantly larger than [Formula: see text]. Furthermore, hydrophobic interactions involving lecithin non-polar tails dominate these binding events, which are also accompanied by dewetting of the receptor binding motif. Through an analysis of fluctuations in the radius of gyration of the receptor-binding domain, its contact maps with lecithin molecules, and distributions of water molecules near the binding region, we elucidate molecular interactions that may play an important role in interactions involving surfactant-type molecules and viruses. We discuss our minimal computational model in the context of lecithin-based liposomal nasal sprays as putative mitigating therapies for COVID-19.

First-passage fingerprints of water diffusion near glutamine surfaces.

The extent to which biological interfaces affect the dynamics of water plays a key role in the exchange of matter and chemical interactions that are essential for life. The density and the mobility of water molecules depend on their proximity to biological interfaces and can play an important role in processes such as protein folding and aggregation. In this work, we study the dynamics of water near glutamine surfaces-a system of interest in studies of neurodegenerative diseases. Combining molecular-dynamics simulations and stochastic modelling, we study how the mean first-passage time and related statistics of water molecules escaping subnanometer-sized regions vary from the interface to the bulk. Our analysis reveals a dynamical complexity that reflects underlying chemical and geometrical properties of the glutamine surfaces. From the first-passage time statistics of water molecules, we infer their space-dependent diffusion coefficient in directions normal to the surfaces. Interestingly, our results suggest that the mobility of water varies over a longer length scale than the chemical potential associated with the water-protein interactions. The synergy of molecular dynamics and first-passage techniques opens the possibility for extracting space-dependent diffusion coefficients in more complex, inhomogeneous environments that are commonplace in living matter.

Wildfire spreading prediction using multimodal data and deep neural network approach.

Predicting wildfire spread behavior is an extremely important task for many countries. On a small scale, it is possible to ensure constant monitoring of the natural landscape through ground means. However, on the scale of large countries, this becomes practically impossible due to remote and vast forest territories. The most promising source of data in this case that can provide global monitoring is remote sensing data. Currently, the main challenge is the development of an effective pipeline that combines geospatial data collection and the application of advanced machine learning algorithms. Most approaches focus on short-term fire spreading prediction and utilize data from unmanned aerial vehicles (UAVs) for this purpose. In this study, we address the challenge of predicting fire spread on a large scale and consider a forecasting horizon ranging from 1 to 5 days. We train a neural network model based on the MA-Net architecture to predict wildfire spread based on environmental and climate data, taking into account spatial distribution features. Estimating the importance of features is another critical issue in fire behavior prediction, so we analyze their contribution to the model's results. According to the experimental results, the most significant features are wind direction and land cover parameters. The F1-score for the predicted burned area varies from 0.64 to 0.68 depending on the day of prediction (from 1 to 5 days). The study was conducted in northern Russian regions and shows promise for further transfer and adaptation to other regions. This geospatial data-based artificial intelligence (AI) approach can be beneficial for supporting emergency systems and facilitating rapid decision-making.

Statistical physics of inhomogeneous transport: Unification of diffusion laws and inference from first-passage statistics.

Characterization of composite materials, whose properties vary in space over microscopic scales, has become a problem of broad interdisciplinary interest. In particular, estimation of the inhomogeneous transport coefficients, e.g., the diffusion coefficient or the heat conductivity, which shape important processes in biology and engineering, is a challenging task. The analysis of such systems is further complicated because two alternative formulations of the inhomogeneous transport equations exist in the literature-the Smoluchowski and Fokker-Planck equations, which are also related to the so-called Ito-Stratonovich dilemma. Using the theory of statistical physics, we show that the two formulations, usually regarded as distinct models, are physically equivalent. From this result we develop efficient estimates for the transverse space-dependent diffusion coefficient in fluids near a phase boundary. Our method requires only measurements of escape probabilities and mean exit times of molecules leaving a narrow spatial region. We test our estimates in three case studies: (i) a Langevin model of a Büttikker-Landauer ratchet; atomistic molecular-dynamics simulations of liquid-water molecules in contact with (ii) vapor, and (iii) soap (surfactant) film which has promising applications in physical chemistry. Our analysis reveals that near the surfactant monolayer the mobility of water molecules is slowed down almost twice with respect to the bulk liquid. Moreover, the diffusion coefficient of water correlates with the transition from hydrophilic to hydrophobic parts of the film.

An experimental model for the study of well-differentiated and dedifferentiated liposarcoma; deregulation of targetable tyrosine kinase receptors.

Therapeutic progress in well-differentiated/dedifferentiated liposarcoma (WDLPS/DDLPS) is hampered by lack of relevant experimental models, thereby limiting comprehensive molecularly based investigations. Our goal is to bridge this experimental gap by establishing and characterizing an in vitro/in vivo model useful for examining WDLPS/DDLPS molecular pathogenesis and also therapeutic screening and testing. WDLPS/DDLPS cells were isolated from freshly resected human surgical specimens and were phenotypically and molecularly characterized. MDM2 amplification was determined via FISH analysis. Adipogenic differentiation was evaluated using Oil Red O staining and western blotting (WB). Tyrosine kinase receptors' (TKRs) expression in pre-adipocytes, adipocytes, WDLPS, and DDLPS cells was determined via western blot analysis. SCID mouse xenograft growth was assessed after subcutaneous and/or intraperitoneal tumor cell injection. There was enhanced proliferation, migration, invasion, survival, and pro-angiogenic capacity in DDLPS cells vs WDLPS cells. DDLPS cells formed tumors in SCID mice whereas WDLPS did not. WDLPS/DDLPS cells, especially those that exhibited baseline PPARγ expression, partially retained terminal adipogenic differentiation capacity. MDM2 amplification was found in all WDLPS/DDLPS cell strains, CDK4 overexpression was observed in LPS cells as compared with normal adipocytes, and enhanced JUN expression and phosphorylation was seen in DDLPS cells as compared with WDLPS cells. The TKRs: MET, AXL, KIT, and IGF-1R were overexpressed in LPS cells vs normal adipocytes and pre-adipocytes. In conclusion, these newly established cellular and xenograft models can facilitate investigation of liposarcomagenesis, dedifferentiation, and tumor progression. Further studies of the molecular deregulations so identified may lead to improved therapeutic strategies for patients afflicted by these unfavorable malignancies.

Epithelioid sarcoma and unclassified sarcoma with epithelioid features: clinicopathological variables, molecular markers, and a new experimental model.

BACKGROUND: Epithelioid sarcoma (ES) and unclassified sarcoma with epithelioid features (USEF) are clinically and therapeutically unresolved. We compared ES and USEF patients' clinical behavior, treatment, outcome, and molecular marker expression. Furthermore, preclinical ES study models were developed to enable comprehensive benchside investigations. PATIENTS AND METHODS: A database of ES and USEF patients (n = 116) treated since 1992 was created. A clinically annotated ES-USEF tissue microarray (TMA) was assayed for tumor-related markers. Newly established human and commercially available ES cell lines were characterized and tested in vivo. RESULTS: ES and USEF patients presenting with localized disease exhibited 22% and 25% local recurrence rates, 35% and 19% nodal metastasis rates, and 41% and 53% distant metastasis rates (median follow-up, 54 months and 39 months, respectively). The 5- and 10-year disease-specific survival rates were 88% and 43% and 52% and 42% (ES and USEF, respectively). TMA immunohistochemistry identified integrase interactor (INI)-1 loss, cancer antigen 125, and p53 nuclear expression as significantly more common in ES than USEF cases. Both cell lines preserved ES morphological and biochemical characteristics in vitro and in vivo; loss of INI-1 was shown to occur in both lines. CONCLUSIONS: Enhanced knowledge of ES and USEF clinical behavior, marker expression, and molecular determinants, extended via experimental models, will hopefully accelerate development of urgently needed effective targeted therapies for ES and USEF.

Volterra-series approach to stochastic nonlinear dynamics: Linear response of the Van der Pol oscillator driven by white noise.

The Van der Pol equation is a paradigmatic model of relaxation oscillations. This remarkable nonlinear phenomenon of self-sustained oscillatory motion underlies important rhythmic processes in nature and electrical engineering. Relaxation oscillations in a real system are usually coupled to environmental noise, which further enriches their dynamics, but makes theoretical analysis of such systems and determination of the equation parameter values a difficult task. In a companion paper we have proposed an analytic approach to a similar problem for another classical nonlinear model-the bistable Duffing oscillator. Here we extend our techniques to the case of the Van der Pol equation driven by white noise. We analyze the statistics of solutions and propose a method to estimate parameter values from the oscillator's time series. We use experimental data of active oscillations in a biophysical system to demonstrate how our method applies to real observations and can be generalized for more complex models.

Volterra-series approach to stochastic nonlinear dynamics: The Duffing oscillator driven by white noise.

The Duffing oscillator is a paradigm of bistable oscillatory motion in physics, engineering, and biology. Time series of such oscillations are often observed experimentally in a nonlinear system excited by a spontaneously fluctuating force. One is then interested in estimating effective parameter values of the stochastic Duffing model from these observations-a task that has not yielded to simple means of analysis. To this end we derive theoretical formulas for the statistics of the Duffing oscillator's time series. Expanding on our analytical results, we introduce methods of statistical inference for the parameter values of the stochastic Duffing model. By applying our method to time series from stochastic simulations, we accurately reconstruct the underlying Duffing oscillator. This approach is quite straightforward-similar techniques are used with linear Langevin models-and can be applied to time series of bistable oscillations that are frequently observed in experiments.

Dusty plasma experiment to confirm an expression for the decay of autocorrelation functions.

Statistical physicists recently proposed an expression for an autocorrelation function (ACF) [Belousov and Cohen, Phys. Rev. E 94, 062124 (2016)2470-004510.1103/PhysRevE.94.062124] that has, until now, not been tested experimentally. The expression captures the early behavior of the ACF decay, when the ACF is flattened. Using experimental data from a nonequilibrium steady-state dusty plasma, we confirm that the expression's use extends to liquidlike strongly coupled plasmas. A transition in the shape of the ACF is identified, and we suggest that it corresponds to the onset of collisional scattering.

Nonequilibrium Langevin dynamics: A demonstration study of shear flow fluctuations in a simple fluid.

The present paper is based on a recent success of the second-order stochastic fluctuation theory in describing time autocorrelations of equilibrium and nonequilibrium physical systems. In particular, it was shown to yield values of the related deterministic parameters of the Langevin equation for a Couette flow in a microscopic molecular dynamics model of a simple fluid. In this paper we find all the remaining constants of the stochastic dynamics, which then is simulated numerically and compared directly with the original physical system. By using these data, we study in detail the accuracy and precision of a second-order Langevin model for nonequilibrium physical systems theoretically and computationally. We find an intriguing relation between an applied external force and cumulants of the resulting flow fluctuations. This is characterized by a linear dependence of an athermal cumulant ratio, an apposite quantity introduced here. In addition, we discuss how the order of a given Langevin dynamics can be raised systematically by introducing colored noise.

Second-order fluctuation theory and time autocorrelation function for currents.

By using recent developments for the Langevin dynamics of spatially asymmetric systems, we routinely generalize the Onsager-Machlup fluctuation theory of the second order in time. In this form, it becomes applicable to fluctuating variables, including hydrodynamic currents, in equilibrium as well as nonequilibrium steady states. From the solution of the obtained stochastic equations we derive an analytical expression for the time autocorrelation function of a general fluctuating quantity. This theoretical result is then tested in a study of a shear flow by molecular dynamics simulations. The proposed form of the time autocorrelation function yields an excellent fit to our computational data for both equilibrium and nonequilibrium steady states. Unlike the analogous result of the first-order Onsager-Machlup theory, our expression correctly describes the short-time correlations. Its utility is demonstrated in an application of the Green-Kubo formula for the transport coefficient. Curiously, the normalized time autocorrelation function for the shear flow, which only depends on the deterministic part of the fluctuation dynamics, appears independent of the external shear force in the linear nonequilibrium regime.

Langevin equation for systems with a preferred spatial direction.

In this paper, we generalize the theory of Brownian motion and the Onsager-Machlup theory of fluctuations for spatially symmetric systems to equilibrium and nonequilibrium steady-state systems with a preferred spatial direction, due to an external force. To do this, we extend the Langevin equation to include a bias, which is introduced by an external force and alters the Gaussian structure of the system's fluctuations. In addition, by solving this extended equation, we provide a physical interpretation for the statistical properties of the fluctuations in these systems. Connections of the extended Langevin equation with the theory of active Brownian motion are discussed as well.

Skewness of steady-state current fluctuations in nonequilibrium systems.

A skewness of the probability for instantaneous current fluctuations, in a nonequilibrium steady state, is observed experimentally in a dusty plasma. This skewness is attributed to the spatial asymmetry, which is imminent to the nonequilibrium systems due to the external hydrodynamic gradient. Using the modern framework of the large deviation theory, we extend the Onsager-Machlup ansatz for equilibrium fluctuations to systems with a preferred spatial direction, and provide a modulated Gaussian probability distribution, which is tested by simulations. This probability distribution is also of potential interest for other statistical disciplines. Connections with the principles of statistical mechanics, due to Boltzmann and Gibbs, are discussed as well.

Poly (ADP) ribose polymerase inhibition: A potential treatment of malignant peripheral nerve sheath tumor.

Poly (ADP) ribose polymerase (PARP) inhibitors, first evaluated nearly a decade ago, are primarily used in malignancies with known defects in DNA repair genes, such as alterations in breast cancer, early onset 1/2 (BRCA1/2). While no specific mutations in BRCA1/2 have been reported in malignant peripheral nerve sheath tumors (MPNSTs), MPNST cells could be effectively targeted with a PARP inhibitor to drive cells to synthetic lethality due to their complex karyotype and high level of inherent genomic instability. In this study, we assessed the expression levels of PARP1 and PARP2 in MPNST patient tumor samples and correlated these findings with overall survival. We also determined the level of PARP activity in MPNST cell lines. In addition, we evaluated the efficacy of the PARP inhibitor AZD2281 (Olaparib) in MPNST cell lines. We observed decreased MPNST cell proliferation and enhanced apoptosis in vitro at doses similar to, or less than, the doses used in cell lines with established defective DNA repair genes. Furthermore, AZD2281 significantly reduced local growth of MPNST xenografts, decreased the development of macroscopic lung metastases, and increased survival of mice with metastatic disease. Our results suggest that AZD2281 could be an effective therapeutic option in MPNST and should be further investigated for its potential clinical use in this malignancy.

Heterogeneity and immunophenotypic plasticity of malignant cells in human liposarcomas.

Liposarcomas are tumors arising in white adipose tissue (WAT) with avidity for local recurrence. Aggressive dedifferentiated liposarcomas (DDLS) may arise from well-differentiated subtypes (WDLS) upon disease progression, however, this key issue is unresolved due in large part to knowledge gaps about liposarcoma cellular composition. Here, we wished to improve insights into liposarcoma cellular hierarchy. Tumor section analysis indicated that the populations, distinguishable based on the expression of CD34 (a marker of adipocyte progenitors) and CD36 (a marker of adipocyte differentiation), occupy distinct intra-tumoral locations in both WDLS and DDLS. Taking advantage of these markers, we separated cells from a panel of fresh human surgical specimens by fluorescence-activated cell sorting (FACS). Based on chromosome analysis and the culture phenotypes of the composing populations, we demonstrate that malignant cells comprise four mesenchymal populations distinguished by the expression of CD34 and CD36, while vascular (CD31+) and hematopoietic (CD45+) components are non-neoplastic. Finally, we show that mouse xenografts are derivable from both CD36-negative and CD36-positive DDLS cells, and that each population recreates the heterogeneity of CD36 expression in vivo. Combined, our results show that malignant cells in WDLS and DDLS can be classified according to distinct stages of adipogenesis and indicate immunophenotypic plasticity of malignant liposarcoma cells.

Survivin is a viable target for the treatment of malignant peripheral nerve sheath tumors.

PURPOSE: To examine the role of survivin as a therapeutic target in preclinical models of human malignant peripheral nerve sheath tumors (MPNST) EXPERIMENTAL DESIGN: Survivin protein expression levels and subcellular localization were examined immunohistochemically in an MPNST tissue microarray. Human MPNST cells were studied in vitro and in vivo; real-time PCR, Western blotting, and immunocytochemical analyses were used to evaluate survivin expression and localization activation. Cell culture assays were used to evaluate the impact of anti-survivin-specific siRNA inhibition on cell growth and cell-cycle progression and survival. The effect of the small-molecule survivin inhibitor YM155 on local and metastatic MPNST growth was examined in vivo. RESULTS: Survivin was found to be highly expressed in human MPNSTs; enhanced cytoplasmic subcellular localization differentiated MPNSTs from their plexiform neurofibroma premalignant counterparts. Human MPNST cell lines exhibited survivin mRNA and protein overexpression; expression in both nuclear and cytoplasmic compartments was noted. Survivin knockdown abrogated MPNST cell growth, inducing G(2) cell-cycle arrest and marked apoptosis. YM155 inhibited human MPNST xenograft growth and metastasis in severe combined immunodeficient (SCID) mice. Antitumor effects were more pronounced in fast-growing xenografts. CONCLUSIONS: Our studies show an important role for survivin in human MPNST biology. Patients with MPNSTs should be considered for ongoing or future clinical trials that evaluate anti-survivin therapeutic strategies. Most importantly, future investigations should evaluate additional pathways that can be targeted in combination with survivin for maximal synergistic anti-MPNST effects.

Targeting the PI3K/mTOR axis, alone and in combination with autophagy blockade, for the treatment of malignant peripheral nerve sheath tumors.

There is a critical need for efficacious therapeutic strategies to improve the outcome of patients afflicted by malignant peripheral nerve sheath tumors (MPNST). Multiple lines of evidence suggest a role for deregulated phosphoinositide 3-kinase (PI3K)/mTOR signaling in MPNST, making this axis an attractive target for therapeutic manipulation. On the basis of previous observations obtained from in vitro experimentation, here we aimed to assess the effects of PI3K/mTOR blockade on MPNST growth in vivo. The anti-MPNST impact of XL765, a dual PI3K/mTOR inhibitor currently being evaluated in human cancer clinical trials, was tested in two human MPNST xenograft models (STS26T and MPNST724) and an experimental model of pulmonary metastasis (STS26T). XL765 abrogated human MPNST local and metastatic growth in severe combined immunodeficient mice. Notably, this therapeutic approach failed to induce apoptosis in MPNST cells but rather resulted in marked productive autophagy. Importantly, genetic and pharmacologic autophagy blockade reversed apoptotic resistance and resulted in significant PI3K/mTOR inhibition-induced MPNST cell death. The addition of the autophagy inhibitor, chloroquine, to the therapeutic regimen of MPNST xenografts after pretreatment with XL765 resulted in superior antitumor effects as compared with either agent alone. Together, preclinical studies described here expand our previous findings and suggest that PI3K/mTOR inhibition alone and (most importantly) in combination with autophagy blockade may comprise a novel and efficacious therapy for patients harboring MPNST.