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The application of lipid-based nanoparticles for COVID-19 vaccines and transthyretin-mediated amyloidosis treatment have highlighted their potential for translation to cancer therapy. However, their use in delivering drugs to solid tumors is limited by ineffective targeting, heterogeneous organ distribution, systemic inflammatory responses, and insufficient drug accumulation at the tumor. Instead, the use of lipid-based nanoparticles to remotely activate immune system responses is an emerging effective strategy. Despite this approach showing potential for treating hematological cancers, its application to treat solid tumors is hampered by the selection of eligible targets, tumor heterogeneity, and ineffective penetration of activated T cells within the tumor. Notwithstanding, the use of lipid-based nanoparticles for immunotherapy is projected to revolutionize cancer therapy, with the ultimate goal of rendering cancer a chronic disease. However, the translational success is likely to depend on the use of predictive tumor models in preclinical studies, simulating the complexity of the tumor microenvironment (e.g., the fibrotic extracellular matrix that impairs therapeutic outcomes) and stimulating tumor progression. This review compiles recent advances in the field of antitumor lipid-based nanoparticles and highlights emerging therapeutic approaches (e.g., mechanotherapy) to modulate tumor stiffness and improve T cell infiltration, and the use of organoids to better guide therapeutic outcomes.

A hidden Markov model is proposed for the analysis of time-series of daily log-returns of the last 4 years of Bitcoin, Ethereum, Ripple, Litecoin, and Bitcoin Cash. These log-returns are assumed to have a multivariate Gaussian distribution conditionally on a latent Markov process having a finite number of regimes or states. The hidden regimes represent different market phases identified through distinct vectors of expected values and variance–covariance matrices of the log-returns, so that they also differ in terms of volatility. Maximum-likelihood estimation of the model parameters is carried out by the expectation–maximisation algorithm, and regimes are singularly predicted for every time occasion according to the maximum-a-posteriori rule. Results show three positive and three negative phases of the market. In the most recent period, an increasing tendency towards positive regimes is also predicted. A rather heterogeneous correlation structure is estimated, and evidence of structural medium term trend in the correlation of Bitcoin with the other cryptocurrencies is detected.

Interactions between living cells and nanoparticles are extensively studied to enhance the delivery of therapeutics. Nanoparticles size, shape, stiffness, and surface charge are regarded as the main features able to control the fate of cell-nanoparticle interactions. However, the clinical translation of nanotherapies has so far been limited, and there is a need to better understand the biology of cell-nanoparticle interactions. This study investigates the role of cellular mechanosensitive components in cell-nanoparticle interactions. It is demonstrated that the genetic and pharmacologic inhibition of yes-associated protein (YAP), a key component of cancer cell mechanosensing apparatus and Hippo pathway effector, improves nanoparticle internalization in triple-negative breast cancer cells regardless of nanoparticle properties or substrate characteristics. This process occurs through YAP-dependent regulation of endocytic pathways, cell mechanics, and membrane organization. Hence, the study proposes targeting YAP may sensitize triple-negative breast cancer cells to chemotherapy and increase the selectivity of nanotherapy.

Rewiring glucose metabolism toward aerobic glycolysis provides cancer cells with a rapid generation of pyruvate, ATP, and NADH, while pyruvate oxidation to lactate guarantees refueling of oxidized NAD+ to sustain glycolysis. CtPB2, an NADH-dependent transcriptional co-regulator, has been proposed to work as an NADH sensor, linking metabolism to epigenetic transcriptional reprogramming. By integrating metabolomics and transcriptomics in a triple-negative human breast cancer cell line, we show that genetic and pharmacological down-regulation of CtBP2 strongly reduces cell proliferation by modulating the redox balance, nucleotide synthesis, ROS generation, and scavenging. Our data highlight the critical role of NADH in controlling the oncogene-dependent crosstalk between metabolism and the epigenetically mediated transcriptional program that sustains energetic and anabolic demands in cancer cells.

We provide an analysis of the market data of the major cryptocurrencies by summing a multivariate hidden Markov process also known as the latent Markov process. We model jointly the daily log-returns of BTC, ETH, XRP, LTC, and BCH. The observed log-returns are assumed to be correlated according to a variance-covariance matrix conditionally on a latent Markov process of first-order having a discrete number of latent states. In order to compare states according to their volatility, we estimate the specific variance-covariance matrix of each state. Maximum likelihood estimation of the model parameters is carried out by the Expectation-Maximization algorithm. The latent states can be ordered according to expected average values of the log-returns and their estimated volatility. We consider different model specifications in terms of number of latent states, which are identified in terms of expected log-returns and level of volatility. Under each considered scenario we also predict the latent state by the maximum a posteriori rule.

Reconfiguring the structure and selectivity of existing chemotherapeutics represents an opportunity for developing novel tumor-selective drugs. Here, as a proof-of-concept, the use of high-frequency sound waves is demonstrated to transform the nonselective anthracycline doxorubicin into a tumor selective drug molecule. The transformed drug self-aggregates in water to form ≈200 nm nanodrugs without requiring organic solvents, chemical agents, or surfactants. The nanodrugs preferentially interact with lipid rafts in the mitochondria of cancer cells. The mitochondrial localization of the nanodrugs plays a key role in inducing reactive oxygen species mediated selective death of breast cancer, colorectal carcinoma, ovarian carcinoma, and drug-resistant cell lines. Only marginal cytotoxicity (80-100% cell viability) toward fibroblasts and cardiomyocytes is observed, even after administration of high doses of the nanodrug (25-40 µg mL-1 ). Penetration, cytotoxicity, and selectivity of the nanodrugs in tumor-mimicking tissues are validated by using a 3D coculture of cancer and healthy cells and 3D cell-collagen constructs in a perfusion bioreactor. The nanodrugs exhibit tropism for lung and limited accumulation in the liver and spleen, as suggested by in vivo biodistribution studies. The results highlight the potential of this approach to transform the structure and bioactivity of anticancer drugs and antibiotics bearing sono-active moieties.

Real-time detection and nanoscale imaging of human immunodeficiency virus type 1 ribonucleic acid (HIV-1 RNA) in latently infected cells that persist in people living with HIV-1 on antiretroviral therapy in blood and tissue may reveal new insights needed to cure HIV-1 infection. Herein, we develop a strategy combining DNA nanotechnology and super-resolution expansion microscopy (ExM) to detect and image a 22 base sequence transcribed from the HIV-1 promoter in model live and fixed cells. We engineer a chimeric locked nucleic acid (LNA)-DNA sensor via hybridization chain reaction to probe HIV-1 RNA in the U3 region of the HIV-1 long terminal repeat (LTR) by signal amplification in live cells. We find that the viral RNA transcript of the U3 region of the HIV-1 LTR, namely PromA, is a valid and specific biomarker to detect infected live cells. The efficiency and selectivity of the LNA-DNA sensor are evaluated in combination with ExM. Unlike standard ExM methods, which rely on additional custom linkers to anchor and immobilize RNA molecules in the intracellular polymeric network, in the current strategy, we probe and image the HIV-1 RNA target at nanoscale resolution, without resorting to chemical linkers or additional preparation steps. This is achieved by physical entrapment of the HIV-1 viral transcripts in the cells post-expansion by finely tuning the mesh size of the intracellular polymeric network.

Engineered nanoparticles for the encapsulation of bioactive agents hold promise to improve disease diagnosis, prevention and therapy. To advance this field and enable clinical translation, the rational design of nanoparticles with controlled functionalities and a robust understanding of nanoparticle-cell interactions in the complex biological milieu are of paramount importance. Herein, a simple platform obtained through the nanocomplexation of glycogen nanoparticles and albumin is introduced for the delivery of chemotherapeutics in complex multicellular 2D and 3D systems. We found that the dendrimer-like structure of aminated glycogen nanoparticles is key to controlling the multivalent coordination and phase separation of albumin molecules to form stable glycogen-albumin nanocomplexes. The pH-responsive glycogen scaffold conferred the nanocomplexes the ability to undergo partial endosomal escape in tumour, stromal and immune cells while albumin enabled nanocomplexes to cross endothelial cells and carry therapeutic agents. Limited interactions of nanocomplexes with T cells, B cells and natural killer cells derived from human blood were observed. The nanocomplexes can accommodate chemotherapeutic drugs and release them in multicellular 2D and 3D constructs. The drugs loaded on the nanocomplexes retained their cytotoxic activity, which is comparable with the activity of the free drugs. Cancer cells were found to be more sensitive to the drugs in the presence of stromal and immune cells. Penetration and cytotoxicity of the drug-loaded nanocomplexes in tumour mimicking tissues were validated using a 3D multicellular-collagen construct in a perfusion bioreactor. The results highlight a simple and potentially scalable strategy for engineering nanocomplexes made entirely of biological macromolecules with potential use for drug delivery.

Cardiac pathologies are characterized by intense remodeling of the extracellular matrix (ECM) that eventually leads to heart failure. Cardiomyocytes respond to the ensuing biomechanical stress by reexpressing fetal contractile proteins via transcriptional and posttranscriptional processes, such as alternative splicing (AS). Here, we demonstrate that the heterogeneous nuclear ribonucleoprotein C (hnRNPC) is up-regulated and relocates to the sarcomeric Z-disc upon ECM pathological remodeling. We show that this is an active site of localized translation, where the ribonucleoprotein associates with the translation machinery. Alterations in hnRNPC expression, phosphorylation, and localization can be mechanically determined and affect the AS of mRNAs involved in mechanotransduction and cardiovascular diseases, including Hippo pathway effector Yes-associated protein 1. We propose that cardiac ECM remodeling serves as a switch in RNA metabolism by affecting an associated regulatory protein of the spliceosome apparatus. These findings offer new insights on the mechanism of mRNA homeostatic mechanoregulation in pathological conditions.

Cardiovascular diseases remain the leading cause of death worldwide; hence there is an increasing focus on developing physiologically relevant in vitro cardiovascular tissue models suitable for studying personalized medicine and pre-clinical tests. Despite recent advances, models that reproduce both tissue complexity and maturation are still limited. We have established a scaffold-free protocol to generate multicellular, beating human cardiac microtissues in vitro from hiPSCs-namely human organotypic cardiac microtissues (hOCMTs)-that show some degree of self-organization and can be cultured for long term. This is achieved by the differentiation of hiPSC in 2D monolayer culture towards cardiovascular lineage, followed by further aggregation on low-attachment culture dishes in 3D. The generated hOCMTs contain multiple cell types that physiologically compose the heart and beat without external stimuli for more than 100 days. We have shown that 3D hOCMTs display improved cardiac specification, survival and metabolic maturation as compared to standard monolayer cardiac differentiation. We also confirmed the functionality of hOCMTs by their response to cardioactive drugs in long-term culture. Furthermore, we demonstrated that they could be used to study chemotherapy-induced cardiotoxicity. Due to showing a tendency for self-organization, cellular heterogeneity, and functionality in our 3D microtissues over extended culture time, we could also confirm these constructs as human cardiac organoids (hCOs). This study could help to develop more physiologically-relevant cardiac tissue models, and represent a powerful platform for future translational research in cardiovascular biology.

Correction to: Vrbský, J., Vinarský, V., Perestrelo, A. R., De La Cruz, J. O., Martino, F., Pompeiano, A., Izzi, V., Hlinomaz, O., Rotrekl, V., Sudol, M., Pagliari, S., & Forte, G. (2021). Evidence for discrete modes of YAP1 signaling via mRNA splice isoforms in development and diseases. Genomics, 113(3), 1349–1365. https://doi.org/10.1016/j.ygeno.2021.03.009 Rinnakkaistallennettu versio / Self-archived version