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Intercellular communication between different cell types in solid tumors contributes to tumor growth and metastatic dissemination. The secretome of cancer-associated fibroblasts (CAFs) plays major roles in these processes. Using human mammary CAFs, we showed that CAFs with a myofibroblast phenotype released extracellular vesicles that transferred proteins to endothelial cells (ECs) that affected their interaction with immune cells. Mass spectrometry-based proteomics identified proteins transferred from CAFs to ECs, which included plasma membrane receptors. Using THY1 as an example of a transferred plasma membrane-bound protein, we showed that CAF-derived proteins increased the adhesion of a monocyte cell line to ECs. CAFs produced high amounts of matrix-bound EVs, which were the primary vehicles of protein transfer. Hence, our work paves the way for future studies that investigate how CAF-derived matrix-bound EVs influence tumor pathology by regulating the function of neighboring cancer, stromal, and immune cells.

Altered eIF4A1 activity promotes translation of highly structured, eIF4A1-dependent oncogene mRNAs at root of oncogenic translational programmes. It remains unclear how these mRNAs recruit and activate eIF4A1 unwinding specifically to facilitate their preferential translation. Here, we show that single-stranded RNA sequence motifs specifically activate eIF4A1 unwinding allowing local RNA structural rearrangement and translation of eIF4A1-dependent mRNAs in cells. Our data demonstrate that eIF4A1-dependent mRNAs contain AG-rich motifs within their 5'UTR which specifically activate eIF4A1 unwinding of local RNA structure to facilitate translation. This mode of eIF4A1 regulation is used by mRNAs encoding components of mTORC-signalling and cell cycle progression, and renders these mRNAs particularly sensitive to eIF4A1-inhibition. Mechanistically, we show that binding of eIF4A1 to AG-rich sequences leads to multimerization of eIF4A1 with eIF4A1 subunits performing distinct enzymatic activities. Our structural data suggest that RNA-binding of multimeric eIF4A1 induces conformational changes in the RNA resulting in an optimal positioning of eIF4A1 proximal to the RNA duplex enabling efficient unwinding. Our data proposes a model in which AG-motifs in the 5'UTR of eIF4A1-dependent mRNAs specifically activate eIF4A1, enabling assembly of the helicase-competent multimeric eIF4A1 complex, and positioning these complexes proximal to stable localised RNA structure allowing ribosomal subunit scanning., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The formation of a functional blood vessel network relies on the ability of endothelial cells (ECs) to dynamically rearrange their adhesive contacts in response to blood flow and guidance cues, such as vascular endothelial growth factor-A (VEGF-A) and class 3 semaphorins (SEMA3s). Neuropilin 1 (NRP1) is essential for blood vessel development, independently of its ligands VEGF-A and SEMA3, through poorly understood mechanisms. Grounding on unbiased proteomic analysis, we report here that NRP1 acts as an endocytic chaperone primarily for adhesion receptors on the surface of unstimulated ECs. NRP1 localizes at adherens junctions (AJs) where, interacting with VE-cadherin, promotes its basal internalization-dependent turnover and favors vascular permeability initiated by histamine in both cultured ECs and mice. We identify a splice variant of tryptophanyl-tRNA synthetase (mini-WARS) as an unconventionally secreted extracellular inhibitory ligand of NRP1 that, by stabilizing it at the AJs, slows down both VE-cadherin turnover and histamine-elicited endothelial leakage. Thus, our work shows a role for NRP1 as a major regulator of AJs plasticity and reveals how mini-WARS acts as a physiological NRP1 inhibitory ligand in the control of VE-cadherin endocytic turnover and vascular permeability., (© 2022. The Author(s).)

Elevated production of collagen-rich extracellular matrix is a hallmark of cancer-associated fibroblasts (CAFs) and a central driver of cancer aggressiveness. Here we find that proline, a highly abundant amino acid in collagen proteins, is newly synthesized from glutamine in CAFs to make tumour collagen in breast cancer xenografts. PYCR1 is a key enzyme for proline synthesis and highly expressed in the stroma of breast cancer patients and in CAFs. Reducing PYCR1 levels in CAFs is sufficient to reduce tumour collagen production, tumour growth and metastatic spread in vivo and cancer cell proliferation in vitro. Both collagen and glutamine-derived proline synthesis in CAFs are epigenetically upregulated by increased pyruvate dehydrogenase-derived acetyl-CoA levels. PYCR1 is a cancer cell vulnerability and potential target for therapy; therefore, our work provides evidence that targeting PYCR1 may have the additional benefit of halting the production of a pro-tumorigenic extracellular matrix. Our work unveils new roles for CAF metabolism to support pro-tumorigenic collagen production., (© 2022. The Author(s).)

Cancer associated fibroblasts (CAFs) are a major component of the tumour microenvironment in most tumours, and are key mediators of the response to tissue damage caused by tumour growth and invasion, contributing to the observation that tumours behave as 'wounds that do not heal'. CAFs have been shown to play a supporting role in all stages of tumour progression, and this is dependent on the highly secretory phenotype CAFs develop upon activation, of which extracellular matrix (ECM) production is a key element. A collagen rich, stromal ECM has been shown to influence tumour growth and metastasis, exclude immune cells and impede drug delivery, and is associated with poor prognosis in many cancers. CAFs also extensively remodel their metabolism to support cancer cells, however, it is becoming clear that metabolic rewiring also supports intrinsic functions of activated fibroblasts, such as increased ECM production. In this review, we summarise how fibroblasts metabolically regulate ECM production, focussing on collagen production, at the transcriptional, translational and post-translational level, and discuss how this can provide possible strategies for effectively targeting CAF activation and formation of a tumour-promoting stroma., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Kay, Koulouras and Zanivan.)

Minimal absent words (MAWs) are minimal-length oligomers absent from a genome or proteome. Although some artificially synthesized MAWs have deleterious effects, there is still a lack of a strategy for the classification of non-occurring sequences as potentially malicious or benign. In this work, by using Markovian models with multiple-testing correction, we reveal significant absent oligomers, which are statistically expected to exist. This suggests that their absence is due to negative selection. We survey genomes and proteomes covering the diversity of life and find thousands of significant absent sequences. Common significant MAWs are often mono- or dinucleotide tracts, or palindromic. Significant viral MAWs are often restriction sites and may indicate unknown restriction motifs. Surprisingly, significant mammal genome MAWs are often present, but rare, in other mammals, suggesting that they are suppressed but not completely forbidden. Significant human MAWs are frequently present in prokaryotes, suggesting immune function, but rarely present in human viruses, indicating viral mimicry of the host. More than one-fourth of human proteins are one substitution away from containing a significant MAW, with the majority of replacements being predicted harmful. We provide a web-based, interactive database of significant MAWs across genomes and proteomes., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

This paper reports an attempt to use ultra-low-frequency (ULF) magnetic field data from a space weather monitoring magnetometer array in the study of earthquake (EQ) precursors in Greece. The data from four magnetometer stations of the Hell ENI c G eo M agnetic A rray ( ENIGMA ) have been analyzed in the search for possible precursors to a strong EQ that occurred south of Lesvos Island on 12 June 2017, with magnitude Mw = 6.3 and focal depth = 12 km. The analysis includes conventional statistical methods, as well as criticality analysis, using two independent methods, the natural time (NT) method and the method of critical fluctuations (MCF). In terms of conventional statistical methods, it is found that the most convincing ULF precursor was observed in the data of ULF (20-30 mHz) depression (depression of the horizontal component of the magnetic field), which is indicative of lower ionospheric perturbation just 1 day before the EQ. Additionally, there are indications of a precursor in the direct ULF emission from the lithosphere 4 days to 1 day before the EQ. Further study in terms of NT analysis identifies criticality characteristics from 8 to 2 days before the EQ both for lithospheric ULF emission and ULF depression, while MCF reveals indications of criticality in all recorded magnetic field components, extending from 10 to 3 days before the EQ. Beyond the recordings of the geomagnetic stations of ENIGMA, the recordings of the fracto-electromagnetic emission stations of the H EL lenic S eismo- E lectro M agnetics Net work ( ELSEM-Net ) in Greece have been analyzed. The MHz recordings at the station that is located on Lesvos Island presented criticality characteristics (by means of both NT analysis and MCF) 11 days before the EQ, while a few days later (7-6 days before the EQ), the kHz recordings of the same station presented tricritical behavior. It is noted that the magnetosphere was quiet for a period of two weeks before the EQ and including its occurrence.

Understanding protein dynamics is crucial in order to elucidate protein function and interactions. Advances in modern microscopy facilitate the exploration of the mobility of fluorescently tagged proteins within living cells. Fluorescence recovery after photobleaching (FRAP) is an increasingly popular functional live-cell imaging technique which enables the study of the dynamic properties of proteins at a single-cell level. As an increasing number of labs generate FRAP datasets, there is a need for fast, interactive and user-friendly applications that analyze the resulting data. Here we present easyFRAP-web, a web application that simplifies the qualitative and quantitative analysis of FRAP datasets. EasyFRAP-web permits quick analysis of FRAP datasets through an intuitive web interface with interconnected analysis steps (experimental data assessment, different types of normalization and estimation of curve-derived quantitative parameters). In addition, easyFRAP-web provides dynamic and interactive data visualization and data and figure export for further analysis after every step. We test easyFRAP-web by analyzing FRAP datasets capturing the mobility of the cell cycle regulator Cdt2 in the presence and absence of DNA damage in cultured cells. We show that easyFRAP-web yields results consistent with previous studies and highlights cell-to-cell heterogeneity in the estimated kinetic parameters. EasyFRAP-web is platform-independent and is freely accessible at: https://easyfrap.vmnet.upatras.gr/.

This paper proposes the development of an advanced fuzzy logic controller which aims to perform intelligent automatic control of the yaw movement of wind turbines. The specific fuzzy controller takes into account both the wind velocity and the acceptable yaw error correlation in order to achieve maximum performance efficacy. In this way, the proposed yaw control system is remarkably adaptive to the existing conditions. In this way, the wind turbine is enabled to retain its power output close to its nominal value and at the same time preserve its yaw system from pointless movement. Thorough simulation tests evaluate the proposed system effectiveness.

Objectives: In this work, a simple technique to assess the image quality characteristics of the postprocessed image is developed and an easy to use figure of image quality (FIQ) is introduced. This FIQ characterizes images in terms of resolution and noise. In addition information capacity, defined within the context of Shannon's information theory, was used as an overall image quality index., Materials and Methods: A digital mammographic image was postprocessed with three digital filters. Resolution and noise were calculated via the Modulation Transfer Function (MTF), the coefficient of variation, and the figure of image quality. In addition, frequency dependent parameters such as the noise power spectrum (NPS) and noise equivalent quanta (NEQ) were estimated and used to assess information capacity., Results: FIQs for the "raw image" data and the image processed with the "sharpen edges" filter were found 907.3 and 1906.1, correspondingly. The information capacity values were 60.86 × 10(3) and 78.96 × 10(3) bits/mm(2)., Conclusion: It was found that, after the application of the postprocessing techniques (even commercial nondedicated software) on the raw digital mammograms, MTF, NPS, and NEQ are improved for medium to high spatial frequencies leading to resolving smaller structures in the final image.

This paper addresses the issues of self-organised critical behaviour of soil-radon and MHz-electromagnetic disorders during intense seismic activity in SW Greece. A significant radon signal is re-analysed for environmental influences with Fast Fourier Transform and multivariate statistics. Self-organisation of signals is investigated via fractal evolving techniques and detrended fluctuation analysis. New lengthy radon data are presented and analysed accordingly. The data did not show self-similarities. Similar analysis applied to new important concurrent MHz-electromagnetic signals revealed analogous behaviour to radon. The signals precursory value is discussed., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

This paper focuses on the environmental monitoring of radon in soil as a potential trace gas in the search of earthquake precursors. The paper reports the following: (a) Pre-monitoring experiments. (b) Set-up of methods and devices. (c) Active and passive monitoring results concentrating on two extremely-strong radon anomalies (~ 500 kBq m(-3)). (e) Discussion regarding the employed ± 2σ technique for identifying radon disturbances. (f) Application of wavelet-power-spectrum fractal analysis for detecting power-law behaviour. The strong anomalies exhibited anti-persistent power-law-beta-values (b = (1.8 ± 0.2), b = (1.8 ± 0.3)) significantly higher than those of the baseline. Persistent b-values were also detected. The findings comply with a self-organised-critical pre-earthquake state. (h) Discussion on models that interpret the radon anomalies focusing on the recently-proposed asperity-model. (i) Application of a recent technique which showed that the two strong disturbances were proportional to the strain change. It was concluded that the strong radon disturbances may be linked to the strong earthquake of 8/6/2008, M = 6.5, occurred 29 km away from the installed instrumentation.