Roadmap on semiconductor-cell biointerfaces.

This roadmap outlines the role semiconductor-based materials play in understanding the complex biophysical dynamics at multiple length scales, as well as the design and implementation of next-generation electronic, optoelectronic, and mechanical devices for biointerfaces. The roadmap emphasizes the advantages of semiconductor building blocks in interfacing, monitoring, and manipulating the activity of biological components, and discusses the possibility of using active semiconductor-cell interfaces for discovering new signaling processes in the biological world

Selective cell death of latently HIV-infected CD4+ T cells mediated by autosis inducing nanopeptides.

Despite significant advances in the treatment of human immunodeficiency virus type-1 (HIV) infection, antiretroviral therapy only suppresses viral replication but is unable to eliminate infection. Thus, discontinuation of antiretrovirals results in viral reactivation and disease progression. A major reservoir of HIV latent infection resides in resting central memory CD4+ T cells (TCM) that escape clearance by current therapeutic regimens and will require novel strategies for elimination. Here, we evaluated the therapeutic potential of autophagy-inducing peptides, Tat-Beclin 1 and Tat-vFLIP-α2, which can induce a novel Na+/K+-ATPase dependent form of cell death (autosis), to kill latently HIV-infected TCM while preventing virologic rebound. In this study, we encapsulated autophagy inducing peptides into biodegradable lipid-coated hybrid PLGA (poly lactic-co-glycolic acid) nanoparticles for controlled intracellular delivery. A single dose of nanopeptides was found to eliminate latent HIV infection in an in vitro primary model of HIV latency and ex vivo using resting CD4+ T cells obtained from peripheral blood mononuclear cells of HIV-infected patients on antiretroviral with fully suppressed virus for greater than 12 months. Notably, increased LC3B lipidation, SQSTM1/p62 degradation and Na+/K+-ATPase activity characteristic of autosis, were detected in nanopeptide treated latently HIV-infected cells compared to untreated uninfected or infected cells. Nanopeptide-induced cell death could be reversed by knockdown of autophagy proteins, ATG5 and ATG7, and inhibition or knockdown of Na+/K+-ATPase. Importantly, viral rebound was not detected following the induction of the Na+/K+-ATPase dependent form of cell death induced by the Tat-Beclin 1 and Tat-vFLIP-α2 nanopeptides. These findings provide a novel strategy to eradicate HIV latently infected resting memory CD4+ T cells, the major reservoir of HIV latency, through the induction of Na+/K+-ATPase dependent autophagy, while preventing reactivation of virus and new infection of uninfected bystander cells

Molecular access to multi-dimensionally encoded information

Polymer scientist have only recently realized that information storage on the molecular level is not only restricted to DNA-based systems. Similar encoding and decoding of data have been demonstrated on synthetic polymers that could overcome some of the drawbacks associated with DNA, such as the ability to make use of a larger monomer alphabet. This feature article describes some of the recent data storage strategies that were investigated, ranging from writing information on linear sequence-defined macromolecules up to layer-by-layer casted surfaces and QR codes. In addition, some strategies to increase storage density are elaborated and some trends regarding future perspectives on molecular data storage from the literature are critically evaluated. This work ends with highlighting the demand for new strategies setting up reliable solutions for future data management technologies

A New method for Analysis of Biomolecules Using the BSM-SG Atomic Models

Biomolecules and particularly proteins and DNA exhibit some mysterious features that cannot find satisfactory explanation by quantum mechanical modes of atoms. One of them, known as a Levinthal’s paradox, is the ability to preserve their complex three-dimensional structure in appropriate environments. Another one is that they possess some unknown energy mechanism. The Basic Structures of Matter Supergravitation Unified Theory (BSM-SG) allows uncovering the real physical structures of the elementary particles and their spatial arrangement in atomic nuclei. The resulting physical models of the atoms are characterized by the same interaction energies as the quantum mechanical models, while the structure of the elementary particles influence their spatial arrangement in the nuclei. The resulting atomic models with fully identifiable parameters and angular positions of the quantum orbits permit studying the physical conditions behind the structural and bonding restrictions of the atoms connected in molecules. A new method for a theoretical analysis of biomolecules is proposed. The analysis of a DNA molecule leads to formulation of hypotheses about the energy storage mechanism in DNA and its role in the cell cycle synchronization. This permits shedding a light on the DNA feature known as a C-value paradox. The analysis of a tRNA molecule leads to formulation of a hypothesis about a binary decoding mechanism behind the 20 flavors of the complex aminoacyle-tRNA synthetases - tRNA, known as a paradox

A–C Estrogens as Potent and Selective Estrogen Receptor-Beta Agonists (SERBAs) to Enhance Memory Consolidation under Low-Estrogen Conditions

Estrogen receptor-beta (ERβ) is a drug target for memory consolidation in postmenopausal women. Herein is reported a series of potent and selective ERβ agonists (SERBAs) with in vivo efficacy that are A–C estrogens, lacking the B and D estrogen rings. The most potent and selective A–C estrogen is selective for activating ER relative to seven other nuclear hormone receptors, with a surprising 750-fold selectivity for the β over α isoform and with EC50s of 20–30 nM in cell-based and direct binding assays. Comparison of potency in different assays suggests that the ER isoform selectivity is related to the compound’s ability to drive the productive conformational change needed to activate transcription. The compound also shows in vivo efficacy after microinfusion into the dorsal hippocampus and after intraperitoneal injection (0.5 mg/kg) or oral gavage (0.5 mg/kg). This simple yet novel A–C estrogen is selective, brain penetrant, and facilitates memory consolidation

Synthesizing the role of epigenetics in the response and adaptation of species to climate change in freshwater ecosystems

Freshwater ecosystems are amongst the most threatened ecosystems on Earth. Currently, climate change is one of the most important drivers of freshwater transformation and its effects include changes in the composition, biodiversity and functioning of freshwater ecosystems. Understanding the capacity of freshwater species to tolerate the environmental fluctuations induced by climate change is critical to the development of effective conservation strategies. In the last few years, epigenetic mechanisms were increasingly put forward in this context because of their pivotal role in gene-environment interactions. In addition, the evolutionary role of epigenetically inherited phenotypes is a relatively recent but promising field. Here, we examine and synthesize the impacts of climate change on freshwater ecosystems, exploring the potential role of epigenetic mechanisms in both short- and long-term adaptation of species. Following this wrapping-up of current evidence, we particularly focused on bringing together the most promising future research avenues towards a better understanding of the effects of climate change on freshwater biodiversity, specifically highlighting potential molecular targets and the most suitable freshwater species for future epigenetic studies in this context