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The ionosphere is an ionized part of the upper atmosphere, where the number of electrons in is large enough to affect the propagation of electromagnetic signals, including those of the GNSS systems. Therefore, knowing electron density values in the ionosphere is crucial for both industrial and scientific applications. Here, we employ the radio occultation profiles collected by the CHAMP, GRACE, and COSMIC missions, to model the electron density in the topside ionosphere. We assume a linear decay of scale height with altitude and create a model of 4 parameters, namely the F2-peak density and height (NmF2 and hmF2) and the slope and gradient of scale height in the topside (H0 and dHs/dh). The resulting model (NET) is based on feedforward neural networks and takes as input the geographic and geomagnetic position, the solar flux and geomagnetic indices. The resulting density reconstructions are validated on more than a hundred million in-situ measurements from CHAMP, CNOFS and Swarm satellites, as well as on the GRACE/KBR data, and the developed model is compared to several topside options of the Internation Reference Ionosphere (IRI) model. The NET model yields highly accurate reconstructions of electron density in the topside ionosphere and gives unbiased predictions for all seasonal and solar activity conditions.

There have been a number of theories proposed concerning the loss of relativistic electrons from the radiation belts. However, direct observations of loss were not possible on a number of previous missions due to the large field of view of the instruments and often high-altitude orbits of satellites that did not allow researchers to isolate the precipitating electrons from the stably trapped. We use measurements from the ELFIN-L suit of instruments flown on Lomonosov spacecraft at LEO orbit, which allows us to distinguish stably trapped from the drift loss cone electrons. The sun-synchronous orbit of Lomonosov allows us to quantify scattering that occurred into the loss cone on the dawn-side and the dusk-side magnetosphere. The loss at MeV energies is observed predominantly on the dawn-side, consistent with the loss induced by the chorus waves. The companion data publication provides processed measurements.

The ionosphere is an ionized part of the upper atmosphere, where the number of electrons in is large enough to affect the propagation of electromagnetic signals, including those of the GNSS systems. Therefore, knowing electron density values in the ionosphere is crucial for both industrial and scientific applications. Here, we employ the radio occultation profiles collected by the CHAMP, GRACE, and COSMIC missions, to model the electron density in the topside ionosphere. We assume a linear decay of scale height with altitude and create a model of 4 parameters, namely the F2-peak density and height (NmF2 and hmF2) and the slope and gradient of scale height in the topside (H0 and dHs/dh). The resulting model (NET) is based on feedforward neural networks and takes as input the geographic and geomagnetic position, the solar flux and geomagnetic indices. The resulting density reconstructions are validated on more than a hundred million in-situ measurements from CHAMP, CNOFS and Swarm satellites, as well as on the GRACE/KBR data, and the developed model is compared to several topside options of the Internation Reference Ionosphere (IRI) model. The NET model yields highly accurate reconstructions of electron density in the topside ionosphere and gives unbiased predictions for all seasonal and solar activity conditions.

Generating reliable databases of electron density measurements over a wide range of geomagnetic conditions is essential for improving empirical models of electron density. The Neural-network-based Upper hybrid Resonance Determination (NURD) algorithm has been developed for automated extraction of electron density from Van Allen Probes electric field measurements, and has been shown to be in good agreement with existing semi-automated methods and empirical models. The extracted electron density data has since then been used to develop the PINE (Plasma density in the Inner magnetosphere Neural network-based Empirical) model, an empirical model for reconstructing the global dynamics of the cold plasma density distribution based only on solar wind data and geomagnetic indices. In this study we re-implement the NURD algorithm in both Python and Matlab, and compare the performance of these implementations to each other and previous NURD results. We take advantage of a labeled training data set now being available for the full duration of the Van Allen Probes mission to train the network and generate an electron density data set for a significantly longer time period. We perform detailed comparisons between this output, electron density produced from Van Allen Probes electric field measurements using the AURA semi-automated algorithm, and electron density obtained from existing empirical models. We also present preliminary results from the PINE plasmasphere model trained on this extended NURD electron density data set.

This study introduces a new two-step neural-network based approach for modelling vertical total electron content (VTEC) on a global level. The inputs to the neural network are chosen and evaluated through different feature selection techniques, namely time-lagged Pearson cross-correlation, mutual information, random forests and permutation feature importance. The feature sets consist of geomagnetic and solar wind indices, their time histories and geomagnetic and geographic coordinates. The parameters of the neural networks are tuned with cross validation and the final model is tested in extended time intervals covering a wide range of solar activity conditions. The proposed approach increases computational efficiency and provides with a high generalization skill.

Pitch angle distributions (PADs) of trapped particles play an important role in understanding the processes driving the dynamics of Earth’s radiation belts and ring current. The Van Allen Probes mission has provided electron observations of PADs with an unprecedented coverage in energy (from tens of keV to several MeV) and pitch angles during the mission’s lifespan. We approximate the equatorial electron PADs using the Fourier sine series expansion up to degree 5. The corresponding coefficients can be directly related to the main PAD shapes (pancake, butterfly, flat-top and cap), and the approximated PADs can be easily integrated and converted to omnidirectional flux. Using the entire Van Allen Probes MagEIS data set in 2012-2019, we analyze the response of the equatorial electron PAD shapes to 129 geomagnetic storms with minimum Dst< -50nT. At lower energies (

Satellite observations show that electrons in the Van Allen radiation belts can have energies in excess of 7 MeV. The Van Allen Probes mission not only provided measurements of ultra-relativistic radiation belt electrons, but also simultaneous observations of plasma waves, allowing for the routine inference of total plasma number density. Based on a year of observations from 2015, we show that the electron plasma density has a controlling effect over local chorus acceleration to ultra-relativistic energies, which occurs only when the plasma number density drops down to very low values (~10 cm-3). Results from a Versatile Electron Radiation Belt (VERB) simulation show that a reduced electron plasma density allows chorus waves to efficiently resonate with electrons up to ultra-relativistic energies, producing enhancements from 100s of keV up to >7 MeV via local diffusive acceleration. We analyse statistically the observed chorus wave power during ultra-relativistic enhancement events, considering the contribution from both upper and lower band chorus waves. The Versatile Electron Radiation Belt (VERB) model is also used to recreate an ultra-relativistic electron acceleration event and simulation results are compared to observations, showing close agreement in the evolution when the reduction in electron plasma density is taken into account. The PINE density model allows for the investigation of global magnetospheric density changes during this event. We therefore analyze the how the global cold plasma density changes during ultra-relativistic enhancement events and compare to in-situ point measurements of the plasma density.

In the paper there are shown the investigation results of the mode range of selective laser melting process in the course of which is achieved minimum porosity in samples grown from aluminum powder. The estimate of hardness in different areas of samples is carried out, a single melted track formation is considered. The results have practical significance for the growth aluminum alloy products with the specified structure.

Clinical evidences have shown good results using dermal/epidermal substitutes (DESs) to treat diabetic foot ulcers. Recent studies suggest that, in addition to their scaffold action, DESs may favor wound healing by influencing wound bed inflammatory cells. This study aims to investigate whether DES may influence the inflammatory infiltrate and macrophages polarization toward a reparative phenotype. Fifteen diabetic patients with chronic foot ulcers have been randomly enrolled: 5 treated only by standard of care, served as control group (CG), and 10 treated with DES composed of type 1 bovin collagen (Nevelia, SYMATESE) considered as test group (TG). A biopsy was taken at baseline (T0) and after 30 days (T1). From bioptic paraffin specimen histological, immunohistochemical, and immunofluorescence analysis was performed. Immunohistochemistry reactions evaluated the number of M1 macrophage (CD38+) and M2 macrophage (CD163+). TG patients displayed general macrophage activation and their greater polarization toward M2 subpopulation 30 days after DES implant, compared with CG. From T0 to T1 there was a significant decrease of CD38+ (230 ± 42 and 135 ± 48 mm2, respectively; P < .001) and significant increase of CD163+ (102 ± 21 positive cells/mm2 and 366 ± 42 positive cells/mm2, respectively; P < .001). Confocal microscopy confirmed an increase of M2 cells as expressed by the reduced CD68+/CD163+ ratio. After 6 months of observation 6 patients (60%) of the TG completely healed, while only 1 patient (20%) healed in the CG ( P < .01). The tested DES makes possible to treat diabetic foot ulcers inducing tissue reparative processes through macrophage activation and M2 reparative polarization.

In this study, we perform the first comprehensive comparison of ion density (Ni) in the topside ionosphere measured by the Langmuir probe (LP) and faceplate (FP) of the thermal ion imager on board Swarm satellites. Our results show a systematic difference between the LP and FP derived Ni values, and the systematic difference shows prominent dependences on solar flux, local time, and season. Although both Ni datasets show generally good linear regression with electron density (Ne) measurements from the incoherent scatter radar (ISR) located at Jicamarca, the Ni derived from LP shows an additional dependence on the solar flux, while such a dependence cannot be seen in the FP-derived Ni. We suggest that the solar flux dependence of LP-derived Ni is related to the ion compositions change at Swarm altitude, which has not been properly accounted for in the LP processing algorithm. More light ions (e.g., H+), diffusing down from the plasmasphere to the Swarm altitude, seem to cause the overestimation of Ni from LP during low solar activity. A linear relation between the Swarm LP-derived Ni and ISR Ne is derived, and such a function is recommended to be implemented into further updates of the Swarm LP plasma density data.

Over the last 20 years, a large number of instruments have provided plasma density measurements in Earth's topside ionosphere. To utilize all of the collected observations for empirical modeling, it is necessary to ensure that they do not exhibit systematic differences and are adjusted to the same reference frame. In this study, we compare satellite plasma density observations from Gravity Recovery and Climate Experiment (GRACE), Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC), CHAllenging Minisatellite Payload (CHAMP), Swarm, and Communications/Navigation Outage Forecasting System (C/NOFS) missions. Electron densities retrieved from GRACE K‐Band Ranging (KBR) system, previously shown to be in excellent agreement with incoherent scatter radar (ISR) measurements, are used as a reference. We find that COSMIC radio occultation (RO) densities are highly consistent with GRACE‐KBR observations showing a mean relative difference of, Key Points: A systematic comparison of the plasma density data from CHAMP, C/NOFS, GRACE, COSMIC, and Swarm missions is performed. Electron densities retrieved from COSMIC‐RO agree well with GRACE‐KBR observations showing a relative difference of less than 2%. Intercalibration factors, allowing to eliminate the systematic offsets between the considered data sets, are presented., Helmholtz Pilot Projects Information & Data Science II, MAchine learning based Plasma density model project, National Center for Atmospheric Research http://dx.doi.org/10.13039/100005323, Air Force Office of Scientific Research http://dx.doi.org/10.13039/100000181, National Science Foundation http://dx.doi.org/10.13039/100000001

A new approach to identify the signals of the Earth’s main magnetic field (core field) based on the magnetic observatory data processing is suggested. The algorithms implemented in the approach are based on the Discrete mathematical analysis (DMA). The developed method is used to analyze the data from 49 midand low-latitude observatories of the INTERMAGNET network collected in 2011–2015. The results are compared with the classical method for determining the periods of low magnetic activity of external origin which is adopted by the International Association for Geomagnetism and Aeronomy (IAGA). The advantages of the suggested new approach are demonstrated. Based on the data records for the selected time intervals, the time series of the core field components and their secular variations are obtained for each observatory. These data are compared to the values predicted by the most accurate core field models: SIFM, CHAOS-6, and EMM-2015. The accuracy of the models is estimated using a set of statistical parameters: Pearson’s coefficient of linear correlation, Spearman’s and Kendall’s coefficients of rank correlation, the mean and median values over the data sets, and the mean difference between the data obtained by the suggested method from observatory measurements and the model predictions.

Ionosphere is the ionized layer of the Earth’s upper atmosphere. Vertical total electron content (VTEC) is a highly descriptive measure of the ionosphere. Modeling and predicting VTEC is crucial, because its disturbances are indicative of severe effects in GPS signal propagation and radio communication. We present a new neural-network-based model of VTEC parametrized with geomagnetic indices, solar wind and their time histories. The model was extensively validated with nested cross-validation to ensure that it performs well during geomagnetic storms and quiet times. We applied a number of feature selection methods, namely gradient boosting, permutation feature importance, random forests and cross-correlation. We selected the best input parameters to the model. In addition to reducing dimensionality and avoiding overfitting, the proposed approach also allows to get physical insights into the dynamics of the ionosphere.

Electrons in the Van Allen radiation belts can have energies in excess of 7 MeV. We present a unique way of analyzing phase space density data which demonstrates that local acceleration is capable of heating electrons up to 7 MeV. The Van Allen Probes mission not only provided unique measurements of ultra-relativistic radiation belt electrons, but also simultaneous observations of plasma waves that allowed for the routine inference of total plasma number density. Based on long-term observations, we show that the underlying plasma density has a controlling effect over local acceleration to ultra-relativistic energies, which occurs only when the plasma number density drops down to very low values (~10 cm-3). The VERB-2D model is used to simulate ultra-relativistic electron acceleration during an event which exhibits an extreme cold plasma depletion. The results show that a reduced electron plasma density allows chorus waves to efficiently resonate with electrons up to ultra-relativistic energies, producing enhancements from 100s of keV up to >7 MeV via local diffusive acceleration. We analyse statistically the observed chorus wave power during ultra-relativistic enhancement events, considering the contribution from both upper and lower band chorus waves. The PINE density model allows for the investigation of global magnetospheric density changes. We analyze the how the global cold plasma density changes during ultra-relativistic enhancement events and compare to in-situ point measurements of the plasma density.

In this work, we review the results of observations by the Cluster/Research with Adaptive Particle Imaging Detectors (RAPID) energetic charged particle detector (urn:x-wiley:21699380:media:jgra56722:jgra56722-math-000140 keV–urn:x-wiley:21699380:media:jgra56722:jgra56722-math-00021 MeV). The origin of energetic ions in the region upstream of the Earth's bow shock is compared under different solar wind conditions. We give a brief overview of the acceleration mechanisms of charged particles in the plasma sheet. Effective acceleration is associated with (multiple) interaction(s) of charged particles with multiscale magnetic structures and/or electromagnetic fluctuations, which are the consequences of reconnection or other plasma instabilities. The necessity of such acceleration mechanisms to reproduce the distributions of energetic particles on closed magnetic field lines is discussed. We review empirical models describing the distributions of charged particles. Several aspects of the dynamics of energetic particles during substorms and their influence on the dynamics of magnetic storms are shown. We advise to consider including the energetic particles at urn:x-wiley:21699380:media:jgra56722:jgra56722-math-000340 keV in calculations of the plasma temperature and pressure during these dynamic processes.

The transcription factor p63 mediates distinct cellular responses, primarily regulating epithelial and oocyte biology. In addition to the two amino terminal isoforms, TAp63 and ΔNp63, the 3’-end of p63 mRNA undergoes tissue-specific alternative splicing that leads to several isoforms, including p63α, p63β and p63γ. To investigate in vivo how the different isoforms fulfil distinct functions at the cellular and developmental levels, we developed a mouse model replacing the p63α with p63β by deletion of exon 13 in the Trp63 gene. Here, we report that whereas in two organs physiologically expressing p63α, such as thymus and skin, no abnormalities are detected, total infertility is evident in heterozygous female mice. A sharp reduction in the number of primary oocytes during the first week after birth occurs as a consequence of the enhanced expression of the pro-apoptotic transcriptional targets Puma and Noxa by the tetrameric, constitutively active, TAp63β isoform. Hence, these mice show a condition of ovary dysfunction, resembling human primary ovary insufficiency. Our results show that the p63 C-terminus is essential in TAp63α-expressing primary oocytes to control cell death in vivo, expanding the current understanding of human primary ovarian insufficiency., The transcription factor p63 mediates different cellular responses affecting epithelial and oocyte biology. Here, the authors generate a mouse model (HET Δ13p63 mice) expressing the p63β isoform and show this affects ovary development, phenocopying a human syndrome, primary ovary insufficiency.

The Cluster mission has produced a large data set of electron flux measurements in the Earth's magnetosphere since its launch in late 2000. Electron fluxes are measured using Research with Adaptive Particle Imaging Detector (RAPID)/Imaging Electron Spectrometer (IES) detector as a function of energy, pitch angle, spacecraft position, and time. However, no adiabatic invariants have been calculated for Cluster so far. In this paper we present a step-by-step guide to calculations of adiabatic invariants and conversion of the electron flux to phase space density (PSD) in these coordinates. The electron flux is measured in two RAPID/IES energy channels providing pitch angle distribution at energies 39.2-50.5 and 68.1-94.5 keV in nominal mode since 2004. A fitting method allows to expand the conversion of the differential fluxes to the range from 40 to 150 keV. Best data coverage for phase space density in adiabatic invariant coordinates can be obtained for values of second adiabatic invariant, K, similar to 10(2), and values of the first adiabatic invariant mu in the range approximate to 5-20 MeV/G. Furthermore, we describe the production of a new data product "LSTAR," equivalent to the third adiabatic invariant, available through the Cluster Science Archive for years 2001-2018 with 1-min resolution. The produced data set adds to the availability of observations in Earth's radiation belts region and can be used for long-term statistical purposes., Zweitver��ffentlichungen der Universit��t Potsdam : Mathematisch-Naturwissenschaftliche Reihe; 1192

The Kelvin-Helmholtz instability (KHI) and its effects relating to the transfer of energy and mass from the solar wind into the magnetosphere remain an important focus of magnetospheric physics. On...

The radiation belts of the Earth, filled with energetic electrons, comprise complex and dynamic systems that pose a significant threat to satellite operation. While various models of electron flux both for low and relativistic energies have been developed, the behavior of medium energy (120–600 keV) electrons, especially in the MEO region, remains poorly quantified. At these energies, electrons are driven by both convective and diffusive transport, and their prediction usually requires sophisticated 4D modeling codes. In this paper, we present an alternative approach using the Light Gradient Boosting (LightGBM) machine learning algorithm. The Medium Energy electRon fLux In Earth's outer radiatioN belt (MERLIN) model takes as input the satellite position, a combination of geomagnetic indices and solar wind parameters including the time history of velocity, and does not use persistence. MERLIN is trained on >15 years of the GPS electron flux data and tested on more than 1.5 years of measurements. Tenfold cross validation yields that the model predicts the MEO radiation environment well, both in terms of dynamics and amplitudes o f flux. Evaluation on the test set shows high correlation between the predicted and observed electron flux (0.8) and low values of absolute error. The MERLIN model can have wide space weather applications, providing information for the scientific community in the form of radiation belts reconstructions, as well as industry for satellite mission design, nowcast of the MEO environment, and surface charging analysis., Plain Language Summary: The radiation belts of the Earth, which are the zones of charged energetic particles trapped by the geomagnetic field, comprise complex and dynamic systems posing a significant threat to a variety of commercial and military satellites. While the inner belt is relatively stable, the outer belt is highly variable and depends substantially on solar activity; therefore, accurate and improved models of electron flux in the outer radiation belt are essential to understand the underlying physical processes. Although many models have been developed for the geostationary orbit and relativistic energies, prediction of electron flux in the 120–600 keV energy range still remains challenging. We present a data‐driven model of the medium energies (120–600 keV) differentialelectron flux in the outer radiation belt based on machine learning. We use 17 years of electron observations by Global Positioning System (GPS) satellites. We set up a 3D model for flux prediction in terms of L‐values, MLT, and magnetic latitude. The model gives reliable predictions of the radiation environment in the outer radiation belt and has wide space weather applications., Key Points: A machine learning model is created to predict electron flux at MEO for energies 120–600 keV. The model requires solar wind parameters and geomagnetic indices as input and does not use persistence. MERLIN model yields high accuracy and high correlation with observations (0.8)., Horizon 2020 – The EU Research and Innovation programme

Four transglutaminase (TG) isoforms have been detected in epidermal keratinocytes: TG1, TG2, TG3, and TG5. Except for TG1 and TG3, their contribution to keratinocyte development and structure remains undefined. In this paper, we focused on the roles of TG2 and TG3 in imiquimod-induced psoriasis in mouse skin. We evaluated the severity of psoriasis markers in the skin of imiquimod-treated TG3 null and TG2 null mice. Our results showed that compromised TG3KO mouse skin was more responsive than WT or TG2KO mouse skin to the action of the pro-inflammatory drug imiquimod.

Earth’s radiation belts comprise complex and dynamic systems, depending substantially on solar activity. The pitch angle distributions (PADs) play an important role for radiation belts modelling, as they yield information on the particle transport, source and loss processes. Yet, many missions flying in the radiation belts provide omni-directional or uni-directional electron flux measurements and do not resolve pitch angles. We propose an empirical model of the equatorial PADs and a method to retrieve PADs from omni-directional flux measurements at different energies and locations along the inclined orbits. We use the entire dataset of MagEIS and REPT instruments aboard the Van Allen Probes (RBSP) mission to analyze the equatorial pitch angle distributions in the energy range from 30 keV to 6.2 MeV. The fitting method resolves all main types of PADs, including butterfly and cap distributions, and the resulting coefficients are directly related to the PAD shapes. The developed model can be used to obtain pitch angle resolved fluxes for GPS, Arase and other missions. The proposed algorithm is applied to the GPS electron flux data set to obtain the pitch-angle resolved fluxes, which are compared to the RBSP data at a number of GPS-RBSP conjunctions. The proposed model also allows one to reconstruct the pitch-angle resolved data using LEO measurements. The dynamics of the fitting coefficients based on solar activity is discussed with respect to AE, Kp, Dst indices and solar wind parameters: velocity, density and dynamic pressure.

The most regular of all daily geomagnetic field variations is the so-called solar quiet, or Sq, variation. It is attributed to the two current vortices flowing in the E-region of the dayside ionosphere. We present an investigation of the time-dependent parameters of Sq variation for the historical minimum of solar activity in 2008. We apply "Measure of Anomalousness" algorithm to detection of magnetically quiet days. The global maps of seasonal Sq amplitudes of the three orthogonal components are derived using 75 INTERMAGNET and 46 SuperMAG stations at low and middle latitudes. The global Sq amplitudes are compared to the previous Coupled Magnetosphere-Ionosphere-Thermosphere (CMIT) model simulations and show good agreement. Significant variability was found in Sq(X) and Sq(Y) based on the solar activity and latitude, while almost no difference is observed in Sq(Z) for across all latitudes and seasons. We analyze equivalent Sq current system using observatory data from the Australian mainland and narrow European-African latitudinal segment. Sq current system also strongly depends on solar activity, as current vortices are strongest in the local summer-hemisphere and disintegrate during local winter. The dynamics of Sq variation along the solar cycles 23 and 24 is also discussed and compared to Swarm-based spherical harmonic Sq model.

One of the major and unfortunately unforeseen sources of background for the current generation of X-ray telescopes are few tens to hundreds of keV (soft) protons concentrated by the mirrors. One such telescope is the European Space Agency's (ESA) X-ray Multi-Mirror Mission (XMM-Newton). Its observing time lost due to background contamination is about 40\%. This loss of observing time affects all the major broad science goals of this observatory, ranging from cosmology to astrophysics of neutron stars and black holes. The soft proton background could dramatically impact future large X-ray missions such as the ESA planned Athena mission (http://www.the-athena-x-ray-observatory.eu/). Physical processes that trigger this background are still poorly understood. We use a Machine Learning (ML) approach to delineate related important parameters and to develop a model to predict the background contamination using 12 years of XMM observations. As predictors we use the location of satellite, solar and geomagnetic activity parameters. We revealed that the contamination is most strongly related to the distance in southern direction, $Z$, (XMM observations were in the southern hemisphere), the solar wind radial velocity and the location on the magnetospheric magnetic field lines. We derived simple empirical models for the first two individual predictors and an ML model which utilizes an ensemble of the predictors (Extra Trees Regressor) and gives better performance. Based on our analysis, future missions should minimize observations during times associated with high solar wind speed and avoid closed magnetic field lines, especially at the dusk flank region in the southern hemisphere., Comment: 20 pages, 11 figures

The mechanisms that regulate the switch between epidermal progenitor state and differentiation are not fully understood. Recent findings indicate that the chromatin remodelling BAF complex (Brg1‐associated factor complex or SWI/SNF complex) and the transcription factor p63 mutually recruit one another to open chromatin during epidermal differentiation. Here, we identify a long non‐coding transcript that includes an ultraconserved element, uc.291, which physically interacts with ACTL6A and modulates chromatin remodelling to allow differentiation. Loss of uc.291 expression, both in primary keratinocytes and in three‐dimensional skin equivalents, inhibits differentiation as indicated by epidermal differentiation complex genes down‐regulation. ChIP experiments reveal that upon uc.291 depletion, ACTL6A is bound to the differentiation gene promoters and inhibits BAF complex targeting to induce terminal differentiation genes. In the presence of uc.291, the ACTL6A inhibitory effect is released, allowing chromatin changes to promote the expression of differentiation genes. Thus, uc.291 interacts with ACTL6A to modulate chromatin remodelling activity, allowing the transcription of late differentiation genes., The long non‐coding transcript uc.291 contains an ultraconserved region and is upregulated during keratinocyte differentiation. Uc.291 interacts with the BAF‐associated protein ACTL6A to remodel chromatin, promoting late differentiation gene expression.

Development and maintenance of healthy stratified epithelia require the coordination of complex transcriptional programmes. The transcription factor p63, a member of the p53 family, plays a crucial role in epithelial development and homeostasis. Analysis of the p63-dependent transcriptome indicated that one important aspect of p63 functions in epithelial development is the regulation of cell–cell and cell–matrix adhesion programmes. However, limited knowledge exists on the relevant cell–cell adhesion molecules involved in physiological epithelial formation. Similarly, limited data are available to understand if deregulation of the cell–cell adhesion programme is important in tumour formation. Here, using the epidermis as an experimental model with the RNA sequencing approach, we identify a novel p63-regulated gene induced during differentiation, ZNF185. ZNF185 is an actin-cytoskeleton-associated Lin-l 1, Isl-1 and Mec-3 (LIM) domain-containing protein, whose function is poorly known. We found that p63 binds to a specific enhancer region, promoting its expression to sustain epithelial differentiation. ZNF185 silencing strongly impaired keratinocyte differentiation according to gene array analysis. ZNF185 is detected at the cell–cell periphery where it physically interacts with E-cadherin, indicating that it is important to maintain epithelial integrity beyond its pro-differentiation role. Interestingly, poorly differentiated, including head and neck, cervical and oesophageal, squamous cell carcinomas display loss of ZNF185 expression. Together, these studies reinforce that p63 is a crucial gene for maintaining epithelial tissue integrity and support the deregulation of the cell-cell adhesion programme,which plays a critical role in carcinoma development.

The outermost layer of the skin is formed by the cornified envelope (CE), which is the end product of the process of keratinization. This forms a barrier that is essential to protect the internal homeostasis of the organism from the external environment. The process of keratinization proceeds according to a complex and elaborately controlled differentiation program with the coordinated expression of genes encoding specialized components, enzymes, and regulatory molecules. The CE is a specialized structure that replaces the plasma membrane of differentiating keratinocytes and consists of proteins crosslinked by covalent bonds and lipids to form a scaffold. Understanding of the pathologies associated with defects in CE components will help clarify the molecular mechanisms and the physiological endpoints of keratinization. Here, we describe some diseases of keratinization, and give a brief overview on animal models (transgenic and knockout) with defects in the CE formation. Key concepts: The outermost layer of the skin is formed by the cornified envelope (CE). The CE is a specialized structure that replaces the plasma membrane of differentiating keratinocytes. It consists of proteins crosslinked by covalent bonds and lipids to form a scaffold. The CE is essential to provide the barrier function of the epidermis. The transglutaminase enzymes play a major role in the formation of the CE by catalyzing the formation of crosslinks between specific proteins. Mutations in keratin genes cause a wide variety of epidermal and other epithelial disorders. CE lipids contribute in a significant way to the establishment of barrier function of the epidermis by impermeabilizing the cornified cell and participating in the organization of the intercellular lipid lamellae. Defects in proteases result in barrier function abnormalities or skin diseases. The transcription factor p63 is crucial in epidermis formation, maintaining the progenitor-cell populations that are necessary to sustain epithelial development and morphogenesis. Keywords: apoptosis; cornified envelope; keratinization; cell death; transglutaminase; keratinocyte differentiation; cornification; keratinization

The spatial distribution of energetic protons contributes to the understanding of magnetospheric dynamics. Based upon 17 yr of the Cluster/RAPID observations, we have derived machine-learning-based models to predict the proton intensities at energies from 28 to 962 keV in the 3D terrestrial magnetosphere at radial distances between 6 and 22 RE. We used the satellite location and indices for solar, solar wind, and geomagnetic activity as predictors. The results demonstrate that the neural network (multi-layer perceptron regressor) outperforms baseline models based on the k-nearest neighbors and historical binning on average by ∼80% and ∼33%, respectively. The average correlation between the observed and predicted data is about 56%, which is reasonable in light of the complex dynamics of fast-moving energetic protons in the magnetosphere. In addition to a quantitative analysis of the prediction results, we also investigate parameter importance in our model. The most decisive parameters for predicting proton intensities are related to the location—Z geocentric solar ecliptic direction—and the radial distance. Among the activity indices, the solar wind dynamic pressure is the most important. The results have a direct practical application, for instance, for assessing the contamination particle background in the X-ray telescopes for X-ray astronomy orbiting above the radiation belts. To foster reproducible research and to enable the community to build upon our work we publish our complete code, the data, and the weights of trained models. Further description can be found in the GitHub project at https://github.com/Tanveer81/deep_horizon. publishedVersion