Delivery of DNA-Based Therapeutics for Treatment of Chronic Diseases.

Gene therapy and its role in the medical field have evolved drastically in recent decades. Studies aim to define DNA-based medicine as well as encourage innovation and the further development of novel approaches. Gene therapy has been established as an alternative approach to treat a variety of diseases. Its range of mechanistic applicability is wide; gene therapy has the capacity to address the symptoms of disease, the body's ability to fight disease, and in some cases has the ability to cure disease, making it a more attractive intervention than some traditional approaches to treatment (i.e., medicine and surgery). Such versatility also suggests gene therapy has the potential to address a greater number of indications than conventional treatments. Many DNA-based therapies have shown promise in clinical trials, and several have been approved for use in humans. Whereas current treatment regimens for chronic disease often require frequent dosing, DNA-based therapies can produce robust and durable expression of therapeutic genes with fewer treatments. This benefit encourages the application of DNA-based gene therapy to manage chronic diseases, an area where improving efficiency of current treatments is urgent. Here, we provide an overview of two DNA-based gene therapies as well as their delivery methods: adeno associated virus (AAV)-based gene therapy and plasmid DNA (pDNA)-based gene therapy. We will focus on how these therapies have already been utilized to improve treatment of chronic disease, as well as how current literature supports the expansion of these therapies to treat additional chronic indications in the future.

Enhancing In Vivo Electroporation Efficiency through Hyaluronidase: Insights into Plasmid Distribution and Optimization Strategies.

Electroporation (EP) stands out as a promising non-viral plasmid delivery strategy, although achieving optimal transfection efficiency in vivo remains a challenge. A noteworthy advancement in the field of in vivo EP is the application of hyaluronidase, an enzyme with the capacity to degrade hyaluronic acid in the extracellular matrix, which thereby enhances DNA transfer efficiency by 2- to 3-fold. This paper focuses on elucidating the mechanism of hyaluronidase's impact on transfection efficiency. We demonstrate that hyaluronidase promotes a more uniform distribution of plasmid DNA (pDNA) within skeletal muscle. Additionally, our study investigates the effect of the timing of hyaluronidase pretreatment on EP efficiency by including time intervals of 0, 5, and 30 min between hyaluronidase treatment and the application of pulses. Serum levels of the pDNA-encoded transgene reveal a minimal influence of the hyaluronidase pretreatment time on the final serum protein levels following delivery in both mice and rabbit models. Leveraging bioimpedance measurements, we capture morphological changes in muscle induced by hyaluronidase treatment, which result in a varied pDNA distribution. Subsequently, these findings are employed to optimize EP electrical parameters following hyaluronidase treatment in animal models. This paper offers novel insights into the potential of hyaluronidase in enhancing the effectiveness of in vivo EP, as well as guides optimized electroporation strategies following hyaluronidase use.

Identification of new endocrine disruptive transthyretin ligands in polluted waters using pull-down assay coupled to non-target mass spectrometry.

Surface and treated wastewater are contaminated with highly complex mixtures of micropollutants, which may cause numerous adverse effects, often mediated by endocrine disruption. However, there is limited knowledge regarding some important modes of action, such as interference with thyroid hormone (TH) regulation, and the compounds driving these effects. This study describes an effective approach for the identification of compounds with the potential to bind to transthyretin (TTR; protein distributing TH to target tissues), based on their specific separation in a pull-down assay followed by non-target analysis (NTA). The method was optimized with known TTR ligands and applied to complex water samples. The specific separation of TTR ligands provided a substantial reduction of chromatographic features from the original samples. The applied NTA workflow resulted in the identification of 34 structures. Twelve compounds with available standards were quantified in the original extracts and their TH-displacement potency was confirmed. Eleven compounds were discovered as TTR binders for the first time and linear alkylbenzene sulfonates (LAS) were highlighted as contaminants of concern. Pull-down assay combined with NTA proved to be a well-functioning approach for the identification of unknown bioactive compounds in complex mixtures with great application potential across various biological targets and environmental compartments.

Sampling diverse near-optimal solutions via algorithmic quantum annealing.

Sampling a diverse set of high-quality solutions for hard optimization problems is of great practical relevance in many scientific disciplines and applications, such as artificial intelligence and operations research. One of the main open problems is the lack of ergodicity, or mode collapse, for typical stochastic solvers based on Monte Carlo techniques leading to poor generalization or lack of robustness to uncertainties. Currently, there is no universal metric to quantify such performance deficiencies across various solvers. Here, we introduce a new diversity measure for quantifying the number of independent approximate solutions for NP-hard optimization problems. Among others, it allows benchmarking solver performance by a required time-to-diversity (TTD), a generalization of often used time-to-solution (TTS). We illustrate this metric by comparing the sampling power of various quantum annealing strategies. In particular, we show that the inhomogeneous quantum annealing schedules can redistribute and suppress the emergence of topological defects by controlling space-time separated critical fronts, leading to an advantage over standard quantum annealing schedules with respect to both TTS and TTD for finding rare solutions. Using path-integral Monte Carlo simulations for up to 1600 qubits, we demonstrate that nonequilibrium driving of quantum fluctuations, guided by efficient approximate tensor network contractions, can significantly reduce the fraction of hard instances for random frustrated 2D spin glasses with local fields. Specifically, we observe that by creating a class of algorithmic quantum phase transitions, the diversity of solutions can be enhanced by up to 40% with the fraction of hard-to-sample instances reducing by more than 25%.

Quantum phase transition dynamics in the two-dimensional transverse-field Ising model.

The quantum Kibble-Zurek mechanism (QKZM) predicts universal dynamical behavior near the quantum phase transitions (QPTs). It is now well understood for the one-dimensional quantum matter. Higher-dimensional systems, however, remain a challenge, complicated by the fundamentally different character of the associated QPTs and their underlying conformal field theories. In this work, we take the first steps toward theoretical exploration of the QKZM in two dimensions for interacting quantum matter. We study the dynamical crossing of the QPT in the paradigmatic Ising model by a joint effort of modern state-of-the-art numerical methods, including artificial neural networks and tensor networks. As a central result, we quantify universal QKZM behavior close to the QPT. We also note that, upon traversing further into the ferromagnetic regime, deviations from the QKZM prediction appear. We explain the observed behavior by proposing an extended QKZM taking into account spectral information as well as phase ordering. Our work provides a testing platform for higher-dimensional quantum simulators.

A nuclear cAMP microdomain suppresses tumor growth by Hippo pathway inactivation.

Cyclic AMP (cAMP) signaling is localized to multiple spatially distinct microdomains, but the role of cAMP microdomains in cancer cell biology is poorly understood. Here, we present a tunable genetic system that allows us to activate cAMP signaling in specific microdomains. We uncover a nuclear cAMP microdomain that activates a tumor-suppressive pathway in a broad range of cancers by inhibiting YAP, a key effector protein of the Hippo pathway, inside the nucleus. We show that nuclear cAMP induces a LATS-dependent pathway leading to phosphorylation of nuclear YAP solely at serine 397 and export of YAP from the nucleus with no change in YAP protein stability. Thus, nuclear cAMP inhibition of nuclear YAP is distinct from other known mechanisms of Hippo regulation. Pharmacologic targeting of specific cAMP microdomains remains an untapped therapeutic approach for cancer; thus, drugs directed at the nuclear cAMP microdomain may provide avenues for the treatment of cancer.

Impact of diabetes mellitus on outcomes in patients with myocardial infarction according to varying degrees of left ventricular systolic dysfunction.

BACKGROUND: Diabetes mellitus (DM) is known to contribute to unfavorable short- and long-term outcomes in patients with myocardial infarction (MI). Particularly poor outcomes are associated with left ventricular systolic dysfunction after an MI. Our study aimed to compare the short- and long-term outcomes of MI in patients with DM and varying degrees of left ventricular systolic dysfunction with the corresponding outcomes in a non-diabetic control group. METHODS: This analysis focused on patients with MI registered in the Polish National Registry of Acute Coronary Syndrome between 2009 and 2011. For this analysis, diabetic patients were additionally stratified into three subgroups depending on the degree of left ventricular systolic dysfunction, as assessed during their hospitalization for MI. Subsequently, the 30-day, 12-month, and 36-month outcomes in the diabetic study subgroups were compared with those in the corresponding non- -diabetic subgroups. RESULTS: This analysis encompassed a nationwide cohort of 58 123 patients. Twelve- and 36-months mortality was greater in diabetic patients than in non-diabetic patients. The highest 36-months mortality (46.64%) was in the group of patients with DM and reduced ejection fraction (EF) <40%. Multivariate analysis showed diabetes and low EF to be independent risk factors for 36-month mortality, increasing the risk of death by 35% for diabetes and by 30% for each 5-percentage point EF decrease. Higher mortality was observed in older patients, smokers, and patients with ischemic heart disease before the index hospitalization. CONCLUSIONS: Both diabetes and reduced EF proved to be independent risk factors for increased mortality over a long-term follow-up after MI.

Coherent Many-Body Oscillations Induced by a Superposition of Broken Symmetry States in the Wake of a Quantum Phase Transition.

It is now widely accepted that quenches through the critical region of quantum phase transitions result in post-transition states populated with topological defects-analogs of the classical topological defects. However, consequences of the very nonclassical fact that the state after a quench is a superposition of distinct, broken-symmetry vacua with different numbers and locations of defects have remained largely unexplored. We identify coherent quantum oscillations induced by such superpositions in observables complementary to the one involved in symmetry breaking. These oscillations satisfy Kibble-Zurek dynamical scaling laws with the quench rate, with an instantaneous oscillation frequency set primarily by the gap of the system. In addition to the obvious fundamental significance of a superposition of different broken symmetry states, quantum coherent oscillations can be used to verify unitarity and test for imperfections of the experimental implementations of quantum simulators.

Performance of reservoir discretizations in quantum transport simulations.

Quantum transport simulations often use explicit, yet finite, electronic reservoirs. These should converge to the correct continuum limit, albeit with a trade-off between discretization and computational cost. Here, we study this interplay for extended reservoir simulations, where relaxation maintains a bias or temperature drop across the system. Our analysis begins in the non-interacting limit, where we parameterize different discretizations to compare them on an even footing. For many-body systems, we develop a method to estimate the relaxation that best approximates the continuum by controlling virtual transitions in Kramers turnover for the current. While some discretizations are more efficient for calculating currents, there is little benefit with regard to the overall state of the system. Any gains become marginal for many-body, tensor network simulations, where the relative performance of discretizations varies when sweeping other numerical controls. These results indicate that typical reservoir discretizations have little impact on numerical costs for certain computational tools. The choice of a relaxation parameter is nonetheless crucial, and the method we develop provides a reliable estimate of the optimal relaxation for finite reservoirs.

Approximate optimization, sampling, and spin-glass droplet discovery with tensor networks.

We devise a deterministic algorithm to efficiently sample high-quality solutions of certain spin-glass systems that encode hard optimization problems. We employ tensor networks to represent the Gibbs distribution of all possible configurations. Using approximate tensor-network contractions, we are able to efficiently map the low-energy spectrum of some quasi-two-dimensional Hamiltonians. We exploit the local nature of the problems to compute spin-glass droplets geometries, which provides a new form of compression of the low-energy spectrum. It naturally extends to sampling, which otherwise, for exact contraction, is #P-complete. In particular, for one of the hardest known problem-classes devised on chimera graphs known as deceptive cluster loops and for up to 2048 spins, we find on the order of 10^{10} degenerate ground states in a single run of our algorithm, computing better solutions than have been reported on some hard instances. Our gradient-free approach could provide new insight into the structure of disordered spin-glass complexes, with ramifications both for machine learning and noisy intermediate-scale quantum devices.

Crystal structure of the two-dimensional coordination polymer poly[di-µ-bromido-bis-(µ-tetra-hydro-thiophene)-dicopper(I)].

The polymeric title compound, [Cu2Br2(C4H8S)2] n , CP1, represents an example of a two-dimensional coordination polymer resulting from reaction of CuBr with tetra-hydro-thio-phene (THT) in MeCN solution. The two-dimensional layers consist of two different types of rhomboid-shaped dinuclear Cu(µ2-Br)2Cu secondary building units (SBUs); one with a quite loose Cu⋯Cu separation of 3.3348 (10) Šand a second one with a much closer inter-metallic contact of 2.9044 (9) Å. These SBUs are inter-connected through bridging THT ligands, in which the S atom acts as a four-electron donor bridging each Cu(µ2-Br)2Cu unit in a µ2-bonding mode. In the crystal, the layers are linked by very weak C-H⋯·Br hydrogen bonds with H⋯Br distances of 2.95 Å, thus giving rise to a three-dimensional supra-molecular network.

2-Azabutadiene complexes of rhenium(I): S,N-chelated species with photophysical properties heavily governed by the ligand hidden traits.

The reaction of [Re(CO)3(THF)(µ-Br)]2 or [Re(CO)5X] (X = Cl, Br, I) with the diaryl-2-azabutadienes [(RS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CAr2] containing two thioether arms at the 4,4-position forms the luminescent S,N-chelate complexes fac-[(OC)3ReX{(RS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CAr2}] (1a-h). The halide abstraction by silver triflate converts [(OC)3ReCl{(PhS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CPh2}] (1c) to [(OC)3Re(OS([double bond, length as m-dash]O)2CF3){(PhS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CPh2}] (1j) bearing a covalently bound triflate ligand. The cyclic voltammograms reveal reversible S^N ligand-centred reduction and irreversible oxidation waves for all complexes. The crystal structures of nine octahedral complexes have been determined along with that of (NaphtylS)2C[double bond, length as m-dash]C(H)-N[double bond, length as m-dash]CPh2 (L6). A rich system of weak non-covalent intermolecular secondary interactions through CHX(Cl, Br)Re, CHO, COπ(Ph), CHπCO, CHO and CHS contacts has been evidenced. The photophysical properties have been investigated by steady-state and time-resolved absorption (fs transient absorption, fs-TAS) and emission (ns-TCSPC and ps-Streak camera) spectroscopy in 2-MeTHF solution at 298 and 77 K. The emission bands are composed of either singlet (450 < λmax < 535 nm) and/or triplet emissions (at 77 K only, λmax < 640 nm, or appearing as a tail at λ > 600 nm), which decay in a multiexponential manner for the fluorescence (short ps (i.e.

Open System Tensor Networks and Kramers' Crossover for Quantum Transport.

Tensor networks are a powerful tool for many-body ground states with limited entanglement. These methods can nonetheless fail for certain time-dependent processes-such as quantum transport or quenches-where entanglement growth is linear in time. Matrix-product-state decompositions of the resulting out-of-equilibrium states require a bond dimension that grows exponentially, imposing a hard limit on simulation timescales. However, in the case of transport, if the reservoir modes of a closed system are arranged according to their scattering structure, the entanglement growth can be made logarithmic. Here, we apply this ansatz to open systems via extended reservoirs that have explicit relaxation. This enables transport calculations that can access steady states, time dynamics and noise, and periodic driving (e.g., Floquet states). We demonstrate the approach by calculating the transport characteristics of an open, interacting system. These results open a path to scalable and numerically systematic many-body transport calculations with tensor networks.

Breaking the Entanglement Barrier: Tensor Network Simulation of Quantum Transport.

The recognition that large classes of quantum many-body systems have limited entanglement in the ground and low-lying excited states led to dramatic advances in their numerical simulation via so-called tensor networks. However, global dynamics elevates many particles into excited states, and can lead to macroscopic entanglement and the failure of tensor networks. Here, we show that for quantum transport-one of the most important cases of this failure-the fundamental issue is the canonical basis in which the scenario is cast: When particles flow through an interface, they scatter, generating a "bit" of entanglement between spatial regions with each event. The frequency basis naturally captures that-in the long-time limit and in the absence of inelastic scattering-particles tend to flow from a state with one frequency to a state of identical frequency. Recognizing this natural structure yields a striking-potentially exponential in some cases-increase in simulation efficiency, greatly extending the attainable spatial and time scales, and broadening the scope of tensor network simulation to hitherto inaccessible classes of nonequilibrium many-body problems.

Single-Chain Magnet Based on Cobalt(II) Thiocyanate as XXZ Spin Chain.

Invited for the cover of this issue is the group of Michal Rams at Jagiellonian University (Kraków, Poland) and colleagues at Christian-Albrechts-Universität zu Kiel, Friedrich-Schiller-Universität Jena, and Helmholtz-Zentrum Berlin. The image represents a 1D coordination polymer with Co(II) spins that are flipped by photons during an EPR experiment. Read the full text of the article at 10.1002/chem.201903924.

Single-Chain Magnet Based on Cobalt(II) Thiocyanate as XXZ Spin Chain.

The cobalt(II) in [Co(NCS)2 (4-methoxypyridine)2 ]n are linked by pairs of thiocyanate anions into linear chains. In contrast to a previous structure determination, two crystallographically independent cobalt(II) centers have been found to be present. In the antiferromagnetic state, below the critical temperature (Tc =3.94 K) and critical field (Hc =290 Oe), slow relaxations of the ferromagnetic chains are observed. They originate mainly from defects in the magnetic structure, which has been elucidated by micromagnetic Monte Carlo simulations and ac measurements using pristine and defect samples. The energy barriers of the relaxations are Δτ1 =44.9(5) K and Δτ2 =26.0(7) K for long and short spin chains, respectively. The spin excitation energy, measured by using frequency-domain EPR spectroscopy, is 19.1 cm-1 and shifts 0.1 cm-1 due to the magnetic ordering. Ab initio calculations revealed easy-axis anisotropy for both CoII centers, and also an exchange anisotropy Jxx /Jzz of 0.21. The XXZ anisotropic Heisenberg model (solved by using the density renormalization matrix group technique) was used to reconcile the specific heat, susceptibility, and EPR data.

Nucleoplasmic Reticulum Formation in Human Endometrial Cells is Steroid Hormone Responsive and Recruits Nascent Components.

The nuclei of cells may exhibit invaginations of the nuclear envelope under a variety of conditions. These invaginations form a branched network termed the nucleoplasmic reticulum (NR), which may be found in cells in pathological and physiological conditions. While an extensive NR is a hallmark of cellular senescence and shows associations with some cancers, very little is known about the formation of NR in physiological conditions, despite the presence of extensive nuclear invaginations in some cell types such as endometrial cells. Here we show that in these cells the NR is formed in response to reproductive hormones. We demonstrate that oestrogen and progesterone are sufficient to induce NR formation and that this process is reversible without cell division upon removal of the hormonal stimulus. Nascent lamins and phospholipids are incorporated into the invaginations suggesting that there is a dedicated machinery for its formation. The induction of NR in endometrial cells offers a new model to study NR formation and function in physiological conditions.

Symmetry Breaking Bias and the Dynamics of a Quantum Phase Transition.

The Kibble-Zurek mechanism predicts the formation of topological defects and other excitations that quantify how much a quantum system driven across a quantum critical point fails to be adiabatic. We point out that, thanks to the divergent linear susceptibility at the critical point, even a tiny symmetry breaking bias can restore the adiabaticity. The minimal required bias scales like τ_{Q}^{-ßδ/(1+zν)}, where ß, δ, z, ν are the critical exponents and τ_{Q} is a quench time. We test this prediction by DMRG simulations of the quantum Ising chain. It is directly applicable to the recent emulation of quantum phase transition dynamics in the Ising chain with ultracold Rydberg atoms.