Fascin-induced bundling protects actin filaments from disassembly by cofilin

Actin filament turnover plays a central role in shaping actin networks, yet the feedback mechanism between network architecture and filament assembly dynamics remains unclear. The activity of ADF/cofilin, the main protein family responsible for filament disassembly, has been mainly studied at the single filament level. This study unveils that fascin, by crosslinking filaments into bundles, strongly slows down filament disassembly by cofilin. We show that this is due to a markedly slower initiation of the first cofilin clusters, which occurs up to 100-fold slower on large bundles compared with single filaments. In contrast, severing at cofilin cluster boundaries is unaffected by fascin bundling. After the formation of an initial cofilin cluster on a filament within a bundle, we observed the local removal of fascin. Notably, the formation of cofilin clusters on adjacent filaments is highly enhanced, locally. We propose that this interfilament cooperativity arises from the local propagation of the cofilin-induced change in helicity from one filament to the other filaments of the bundle. Overall, taking into account all the above reactions, we reveal that fascin crosslinking slows down the disassembly of actin filaments by cofilin. These findings highlight the important role played by crosslinkers in tuning actin network turnover by modulating the activity of other regulatory proteins.

Building a stable and robust anti-interference DNA dissipation system by eliminating the accumulation of systemic specified errors

BACKGROUND

The emergence of DNA nanotechnology has enabled the systematic design of diverse bionic dissipative behaviors under the precise control of nucleic acid nanodevices. Nevertheless, when compared to the dissipation observed in robust living systems, it is highly desirable to enhance the anti-interference for artificial DNA dissipation to withstand perturbations and facilitate repairs within the complex biological environments.

RESULTS

In this study, we introduce strategically designed "trash cans" to facilitate kinetic control over interferences, transforming the stochastic binding of individual components within a homogeneous solution into a competitive binding process. This approach effectively eliminates incorrect binding and the accumulation of systemic interferences while ensuring a consistent pattern of energy fluctuation from response to silence. Remarkably, even in the presence of numerous interferences differing by only one base, we successfully achieve complete system reset through multiple cycles, effectively restoring the energy level to a minimum.

SIGNIFICANCE

The system was able to operate stably without any adverse effect under conditions of irregular interference, high-abundance interference, and even multiplex interferences including DNA and RNA crosstalk. This work not only provides an effective paradigm for constructing robust DNA dissipation systems but also greatly broadens the potential of DNA dissipation for applications in high-precision molecular recognition and complex biological reaction networks.

The Effect of Retinol Acetate on Liver Fibrosis Depends on the Temporal Features of the Development of Pathology

Background

The effect of vitamin A on the manifestations of liver fibrosis is controversial and establishing the causes of its multidirectional influence is an urgent problem. In the work, the functional characteristics of the liver with Cu-induced fibrosis were determined after the restoration of vitamin A to the control level at the F0/F1 stage.

Methods

In animals with liver fibrosis, classical indicators of physiology, functional activity of the liver, histological, and hematological characteristics were determined; the content of calcium and ROS was determined in bone marrow cells.

Results

It was shown that in the liver with Cu-induced fibrosis, the restoration of vitamin A content to control values after per os injections of a retinol acetate solution at a dose of 0.10 mg (300 IU)/100 g of body weight in the early stages of this pathology development (Fо/F1) was accompanied by: a decrease in the number of immunocompetent cells in the bloodstream to control values; normalization of the amount of calcium ions and ROS in bone marrow cells; restoration to the control level of activity of alkaline phosphatase; an increase in the number of binuclear hepatocytes; and restoration of the dynamics of body weight growth in experimental animals, even against the background of the ongoing action of the hepatotoxic factor.

Conclusion

We came to the conclusion that the multidirectional action of vitamin A, which occurs in liver fibrosis, depends not only on the concentration of vitamin A in the liver but also on temporal characteristics of cellular and metabolic links involved in the adaptive response formation. It was suggested that knowledge of the initial temporal metabolic characteristics and the amount of vitamin A in the liver, taking into account the stages of fibrosis development, can be an effective way to restore the altered homeostatic parameters of the body.

Modeling non-genetic information dynamics in cells using reservoir computing

Virtually all cells use energy-driven, ion-specific membrane pumps to maintain large transmembrane gradients of Na+, K+, Cl-, Mg++, and Ca++, but the corresponding evolutionary benefit remains unclear. We propose that these gradients enable a dynamic and versatile biological system that acquires, analyzes, and responds to environmental information. We hypothesize that environmental signals are transmitted into the cell by ion fluxes along pre-existing gradients through gated ion-specific membrane channels. The consequent changes in cytoplasmic ion concentration can generate a local response or orchestrate global/regional cellular dynamics through wire-like ion fluxes along pre-existing and self-assembling cytoskeleton to engage the endoplasmic reticulum, mitochondria, and nucleus.

Kinetic trapping organizes actin filaments within liquid-like protein droplets

Several actin-binding proteins (ABPs) phase separate to form condensates capable of curating the actin network shapes. Here, we use computational modeling to understand the principles of actin network organization within VASP condensate droplets. Our simulations reveal that the different actin shapes, namely shells, rings, and mixture states are highly dependent on the kinetics of VASP-actin interactions, suggesting that they arise from kinetic trapping. Specifically, we show that reducing the residence time of VASP on actin filaments reduces degree of bundling, thereby promoting assembly of shells rather than rings. We validate the model predictions experimentally using a VASP-mutant with decreased bundling capability. Finally, we investigate the ring opening within deformed droplets and found that the sphere-to-ellipsoid transition is favored under a wide range of filament lengths while the ellipsoid-to-rod transition is only permitted when filaments have a specific range of lengths. Our findings highlight key mechanisms of actin organization within phase-separated ABPs.

CHRFAM7A diversifies human immune adaption through Ca2+ signalling and actin cytoskeleton reorganization

BACKGROUND

Human restricted genes contribute to human specific traits in the immune system. CHRFAM7A, a uniquely human fusion gene, is a negative regulator of the α7 nicotinic acetylcholine receptor (α7 nAChR), the highest Ca2+ conductor of the ACh receptors implicated in innate immunity. Understanding the mechanism of how CHRFAM7A affects the immune system remains unexplored.

METHODS

Two model systems are used, human induced pluripotent stem cells (iPSC) and human primary monocytes, to characterize α7 nAChR function, Ca2+ dynamics and decoders to elucidate the pathway from receptor to phenotype.

FINDINGS

CHRFAM7A/α7 nAChR is identified as a hypomorphic receptor with mitigated Ca2+ influx and prolonged channel closed state. This shifts the Ca2+ reservoir from the extracellular space to the endoplasmic reticulum (ER) leading to Ca2+ dynamic changes. Ca2+ decoder small GTPase Rac1 is then activated, reorganizing the actin cytoskeleton. Observed actin mediated phenotypes include cellular adhesion, motility, phagocytosis and tissue mechanosensation.

INTERPRETATION

CHRFAM7A introduces an additional, human specific, layer to Ca2+ regulation leading to an innate immune gain of function. Through the actin cytoskeleton it drives adaptation to the mechanical properties of the tissue environment leading to an ability to invade previously immune restricted niches. Human genetic diversity predicts profound translational significance as its understanding builds the foundation for successful treatments for infectious diseases, sepsis, and cancer metastasis.

FUNDING

This work is supported in part by the Community Foundation for Greater Buffalo (Kinga Szigeti) and in part by NIH grant R01HL163168 (Yongho Bae).

Single-cell mechanical assay unveils viscoelastic similarities in normal and neoplastic brain cells

Understanding cancer cell mechanics allows for the identification of novel disease mechanisms, diagnostic biomarkers, and targeted therapies. In this study, we utilized our previously established fluid shear stress assay to investigate and compare the viscoelastic properties of normal immortalized human astrocytes and invasive human glioblastoma (GBM) cells when subjected to physiological levels of shear stress that are present in the brain microenvironment. We used a parallel-flow microfluidic shear system and a camera-coupled optical microscope to expose single cells to fluid shear stress and monitor the resulting deformation in real time, respectively. From the video-rate imaging, we fed cell deformation information from digital image correlation into a three-parameter generalized Maxwell model to quantify the nuclear and cytoplasmic viscoelastic properties of single cells. We further quantified actin cytoskeleton density and alignment in immortalized human astrocytes and GBM cells via fluorescence microscopy and image analysis techniques. Results from our study show that contrary to the behavior of many extracranial cells, normal and cancerous brain cells do not exhibit significant differences in their viscoelastic properties. Moreover, we also found that the viscoelastic properties of the nucleus and cytoplasm as well as the actin cytoskeletal densities of both brain cell types are similar. Our work suggests that malignant GBM cells exhibit unique mechanical behaviors not seen in other cancer cell types. These results warrant future studies to elucidate the distinct biophysical characteristics of the brain and reveal novel mechanical attributes of GBM and other primary brain tumors.

Enzymatic cleaving of entangled DNA rings drives scale-dependent rheological trajectories

DNA, which naturally occurs in linear, ring, and supercoiled topologies, frequently undergoes enzyme-driven topological conversion and fragmentation in vivo, enabling it to perform a variety of functions within the cell. In vitro, highly concentrated DNA polymers form entanglements that yield viscoelastic properties dependent on the topologies and lengths of the DNA. Enzyme-driven alterations of DNA size and shape therefore offer a means of designing active materials with programmable viscoelastic properties. Here, we incorporate multi-site restriction endonucleases into dense DNA solutions to linearize and fragment circular DNA molecules. We pair optical tweezers microrheology with differential dynamic microscopy and single-molecule tracking to measure the linear and nonlinear viscoelastic response and transport properties of entangled DNA solutions over a wide range of spatiotemporal scales throughout the course of enzymatic digestion. We show that, at short timescales, relative to the relaxation timescales of the polymers, digestion of these 'topologically-active' fluids initially causes an increase in elasticity and relaxation times followed by a gradual decrease. Conversely, for long timescales, linear viscoelastic moduli exhibit signatures of increasing elasticity. DNA diffusion, likewise, becomes increasingly slowed, in direct opposition to the short-time behavior. We hypothesize that this scale-dependent rheology arises from the population of small DNA fragments, which increases as digestion proceeds, driving self-association of larger fragments via depletion interactions, giving rise to slow relaxation modes of clusters of entangled chains, interspersed among shorter unentangled fragments. While these slow modes likely dominate at long times, they are presumably frozen out in the short-time limit, which instead probes the faster relaxation modes of the unentangled population.

Does the brain behave like a (complex) network? I. Dynamics

Graph theory is now becoming a standard tool in system-level neuroscience. However, endowing observed brain anatomy and dynamics with a complex network structure does not entail that the brain actually works as a network. Asking whether the brain behaves as a network means asking whether network properties count. From the viewpoint of neurophysiology and, possibly, of brain physics, the most substantial issues a network structure may be instrumental in addressing relate to the influence of network properties on brain dynamics and to whether these properties ultimately explain some aspects of brain function. Here, we address the dynamical implications of complex network, examining which aspects and scales of brain activity may be understood to genuinely behave as a network. To do so, we first define the meaning of networkness, and analyse some of its implications. We then examine ways in which brain anatomy and dynamics can be endowed with a network structure and discuss possible ways in which network structure may be shown to represent a genuine organisational principle of brain activity, rather than just a convenient description of its anatomy and dynamics.

Kinetic Asymmetry and Directionality of Nonequilibrium Molecular Systems

Scientists have long been fascinated by the biomolecular machines in living systems that process energy and information to sustain life. The first synthetic molecular rotor capable of performing repeated 360° rotations due to a combination of photo- and thermally activated processes was reported in 1999. The progress in designing different molecular machines in the intervening years has been remarkable, with several outstanding examples appearing in the last few years. Despite the synthetic accomplishments, there remains confusion regarding the fundamental design principles by which the motions of molecules can be controlled, with significant intellectual tension between mechanical and chemical ways of thinking about and describing molecular machines. A thermodynamically consistent analysis of the kinetics of several molecular rotors and pumps shows that while light driven rotors operate by a power-stroke mechanism, kinetic asymmetry-the relative heights of energy barriers-is the sole determinant of the directionality of catalysis driven machines. Power-strokes-the relative depths of energy wells-play no role whatsoever in determining the sign of the directionality. These results, elaborated using trajectory thermodynamics and the nonequilibrium pump equality, show that kinetic asymmetry governs the response of many non-equilibrium chemical phenomena.

Effect of local active fluctuations on structure and dynamics of flexible biopolymers

Active fluctuations play a significant role in the structure and dynamics of biopolymers (e.g. chromatin and cytoskeletal proteins) that are instrumental in the functioning of living cells. For a large range of experimentally accessible length and time scales, these polymers can be represented as flexible chains that are subjected to spatially and temporally varying fluctuating forces. In this work, we introduce a mathematical framework that correlates the spatial and temporal patterns of the fluctuations to different observables that describe the dynamics and conformations of the polymer. We demonstrate the power of this approach by analyzing the case of a point fluctuation on the polymer with an exponential decay of correlation in time with a finite time constant. Specifically, we identify the length and time scale over which the behavior of the polymer exhibits a significant departure from the behavior of a Rouse chain and the range of impact of the fluctuation along the chain. Furthermore, we show that the conformation of the polymer retains the memory of the active fluctuation from earlier times. Altogether, this work sets the basis for understanding and interpreting the role of spatio-temporal patterns of fluctuations in the dynamics, conformation, and functionality of biopolymers in living cells.

Self-Assembly in an Experimentally Realistic Model of Lobed Patchy Colloids

Colloids with lobed architectures have been shown to self-assemble into promising porous structures with potential biomedical applications. The synthesis of these colloids via experiments can be tuned to vary the number and the position of the lobes. However, the polydispersity involving the numbers, sizes, and the dispositions of lobes, that is often observed in particle designs, can significantly affect their self-assembled structures. In this work, we go beyond the uniform lobe size conditions commonly considered in molecular simulations, and probe the effect of polydispersity due to non-uniform lobe sizes by studying self-assembly in three experimentally observable designs of lobed particles (dumbbell, two lobes; trigonal planar, three lobes; and tetrahedral, four lobes), using coarse-grained Langevin dynamics simulations in the NVT ensemble. With increasing polydispersity, we observed the formation of a crystalline structure from a disordered state for the dumbbell system, and a loss of order in the crystalline structures for the trigonal planar system. The tetrahedral system retained a crystalline structure with only a minor loss in compactness. We observed that the effect of polydispersity on the self-assembled morphology of a given system can be minimized by increasing the number of lobes. The polydispersity in the lobe size may also be useful in tuning self-assemblies toward desired structures.

Active oscillatory associative memory

Traditionally, physical models of associative memory assume conditions of equilibrium. Here, we consider a prototypical oscillator model of associative memory and study how active noise sources that drive the system out of equilibrium, as well as nonlinearities in the interactions between the oscillators, affect the associative memory properties of the system. Our simulations show that pattern retrieval under active noise is more robust to the number of learned patterns and noise intensity than under passive noise. To understand this phenomenon, we analytically derive an effective energy correction due to the temporal correlations of active noise in the limit of short correlation decay time. We find that active noise deepens the energy wells corresponding to the patterns by strengthening the oscillator couplings, where the more nonlinear interactions are preferentially enhanced. Using replica theory, we demonstrate qualitative agreement between this effective picture and the retrieval simulations. Our work suggests that the nonlinearity in the oscillator couplings can improve memory under nonequilibrium conditions.

Extracellular matrix biomechanical roles and adaptation in health and disease

Extracellular matrices (ECMs) are dynamic 3D macromolecular networks that exhibit structural characteristics and composition specific to different tissues, serving various biomechanical and regulatory functions. The interactions between ECM macromolecules such as collagen, elastin, glycosaminoglycans (GAGs), proteoglycans (PGs), fibronectin, and laminin, along with matrix effectors and water, contribute to the unique cellular and tissue functional properties during organ development, tissue homoeostasis, remodeling, disease development, and progression. Cells adapt to environmental changes by adjusting the composition and array of ECM components. ECMs, forming the 3D bioscaffolds of our body, provide mechanical support for tissues and organs and respond to the environmental variables influencing growth and final adult body shape in mammals. Different cell types display distinct adaptations to the respective ECM environments. ECMs regulate biological processes by controlling the diffusion of infections and inflammations, sensing and adapting to external stimuli and gravity from the surrounding habitat, and, in the context of cancer, interplaying with and regulating cancer cell invasion and drug resistance. Alterations in the ECM composition in pathological conditions drive adaptive responses of cells and could therefore result in abnormal cell behavior and tissue dysfunction. Understanding the biomechanical functionality, adaptation, and roles of distinct ECMs is essential for research on various pathologies, including cancer progression and multidrug resistance, which is of crucial importance for developing targeted therapies. In this Viewpoint article, we critically present and discuss specific biomechanical functions of ECMs and regulatory adaptation mechanisms in both health and disease, with a particular focus on cancer progression.

Highly flexible PEG-LifeAct constructs act as tunable biomimetic actin crosslinkers

In vitro studies of actin filament networks crosslinked with dynamic actin binding proteins provide critical insights into cytoskeletal mechanics as well as inspiration for new adaptive materials design. However, discontinuous variance in the physiochemical properties of actin binding proteins impedes holistic relationships between crosslinker molecular parameters, network structure, and mechanics. Bio-synthetic constructs composed of synthetic polymer backbones and actin binding motifs would enable crosslinkers with engineered physiochemical properties to directly target the desired structure-property relationships. As a proof of concept, bio-synthetic crosslinkers composed of highly flexible polyethylene glycol (PEG) polymers functionalized with the actin binding peptide LifeAct, are explored as actin crosslinkers. Using bulk rheology and fluorescence microscopy, these constructs are shown to modulate actin filament network structure and mechanics in a contour length dependent manner, while maintaining the stress-stiffening behavior inherent to actin filament networks. These results encourage the design of more diverse and complex peptide-polymer crosslinkers to interrogate and control semi-flexible polymer networks.

Cortactin stabilizes actin branches by bridging activated Arp2/3 to its nucleated actin filament

Regulation of the assembly and turnover of branched actin filament networks nucleated by the Arp2/3 complex is essential during many cellular processes, including cell migration and membrane trafficking. Cortactin is important for actin branch stabilization, but the mechanism by which this occurs is unclear. Given this, we determined the structure of vertebrate cortactin-stabilized Arp2/3 actin branches using cryogenic electron microscopy. We find that cortactin interacts with the new daughter filament nucleated by the Arp2/3 complex at the branch site, rather than the initial mother actin filament. Cortactin preferentially binds activated Arp3. It also stabilizes the F-actin-like interface of activated Arp3 with the first actin subunit of the new filament, and its central repeats extend along successive daughter-filament subunits. The preference of cortactin for activated Arp3 explains its retention at the actin branch and accounts for its synergy with other nucleation-promoting factors in regulating branched actin network dynamics.

Imaging actin organisation and dynamics in 3D

The actin cytoskeleton plays a critical role in cell architecture and the control of fundamental processes including cell division, migration and survival. The dynamics and organisation of F-actin have been widely studied in a breadth of cell types on classical two-dimensional (2D) surfaces. Recent advances in optical microscopy have enabled interrogation of these cytoskeletal networks in cells within three-dimensional (3D) scaffolds, tissues and in vivo. Emerging studies indicate that the dimensionality experienced by cells has a profound impact on the structure and function of the cytoskeleton, with cells in 3D environments exhibiting cytoskeletal arrangements that differ to cells in 2D environments. However, the addition of a third (and fourth, with time) dimension leads to challenges in sample preparation, imaging and analysis, necessitating additional considerations to achieve the required signal-to-noise ratio and spatial and temporal resolution. Here, we summarise the current tools for imaging actin in a 3D context and highlight examples of the importance of this in understanding cytoskeletal biology and the challenges and opportunities in this domain.

Cortactin is in a complex with VE-cadherin and is required for endothelial adherens junction stability through Rap1/Rac1 activation

Vascular permeability is mediated by Cortactin (Cttn) and regulated by several molecules including cyclic-adenosine-monophosphate, small Rho family GTPases and the actin cytoskeleton. However, it is unclear whether Cttn directly interacts with any of the junctional components or if Cttn intervenes with signaling pathways affecting the intercellular contacts and the cytoskeleton. To address these questions, we employed immortalized microvascular myocardial endothelial cells derived from wild-type and Cttn-knock-out mice. We found that lack of Cttn compromised barrier integrity due to fragmented membrane distribution of different junctional proteins. Moreover, immunoprecipitations revealed that Cttn is within the VE-cadherin-based adherens junction complex. In addition, lack of Cttn slowed-down barrier recovery after Ca2+ repletion. The role of Cttn for cAMP-mediated endothelial barrier regulation was analyzed using Forskolin/Rolipram. In contrast to Cttn-KO, WT cells reacted with increased transendothelial electrical resistance. Absence of Cttn disturbed Rap1 and Rac1 activation in Cttn-depleted cells. Surprisingly, despite the absence of Cttn, direct activation of Rac1/Cdc42/RhoA by CN04 increased barrier resistance and induced well-defined cortical actin and intracellular actin bundles. In summary, our data show that Cttn is required for basal barrier integrity by allowing proper membrane distribution of junctional proteins and for cAMP-mediated activation of the Rap1/Rac1 signaling pathway.

Growth-induced collective bending and kinetic trapping of cytoskeletal filaments

Growth and turnover of actin filaments play a crucial role in the construction and maintenance of actin networks within cells. Actin filament growth occurs within limited space and finite subunit resources in the actin cortex. To understand how filament growth shapes the emergent architecture of actin networks, we developed a minimal agent-based model coupling filament mechanics and growth in a limiting subunit pool. We find that rapid filament growth induces kinetic trapping of highly bent actin filaments. Such collective bending patterns are long-lived, organized around nematic defects, and arises from competition between filament polymerization and bending elasticity. The stability of nematic defects and the extent of kinetic trapping are amplified by an increase in the abundance of the actin pool and by crosslinking the network. These findings suggest that kinetic trapping is a robust consequence of growth in crowded environments, providing a route to program shape memory in actin networks.

Self-assembled active actomyosin gels spontaneously curve and wrinkle similar to biological cells and tissues

Living systems adopt a diversity of curved and highly dynamic shapes. These diverse morphologies appear on many length scales, from cells to tissues and organismal scales. The common driving force for these dynamic shape changes are contractile stresses generated by myosin motors in the cell cytoskeleton, that converts chemical energy into mechanical work. A good understanding of how contractile stresses in the cytoskeleton arise into different three-dimensional (3D) shapes and what are the shape selection rules that determine their final configurations is still lacking. To obtain insight into the relevant physical mechanisms, we recreate the actomyosin cytoskeleton in vitro, with precisely controlled composition and initial geometry. A set of actomyosin gel discs, intrinsically identical but of variable initial geometry, dynamically self-organize into a family of 3D shapes, such as domes and wrinkled shapes, without the need for specific preprogramming or additional regulation. Shape deformation is driven by the spontaneous emergence of stress gradients driven by myosin and is encoded in the initial disc radius to thickness aspect ratio, which may indicate shaping scalability. Our results suggest that while the dynamical pathways may depend on the detailed interactions between the different microscopic components within the gel, the final selected shapes obey the general theory of elastic deformations of thin sheets. Altogether, our results emphasize the importance for the emergence of active stress gradients for buckling-driven shape deformations and provide insights on the mechanically induced spontaneous shape transitions in contractile active matter, revealing potential shared mechanisms with living systems across scales.

Reshaping the Syncytial Drosophila Embryo with Cortical Actin Networks: Four Main Steps of Early Development

Drosophila development begins as a syncytium. The large size of the one-cell embryo makes it ideal for studying the structure, regulation, and effects of the cortical actin cytoskeleton. We review four main steps of early development that depend on the actin cortex. At each step, dynamic remodelling of the cortex has specific effects on nuclei within the syncytium. During axial expansion, a cortical actomyosin network assembles and disassembles with the cell cycle, generating cytoplasmic flows that evenly distribute nuclei along the ovoid cell. When nuclei move to the cell periphery, they seed Arp2/3-based actin caps which grow into an array of dome-like compartments that house the nuclei as they divide at the cell cortex. To separate germline nuclei from the soma, posterior germ plasm induces full cleavage of mono-nucleated primordial germ cells from the syncytium. Finally, zygotic gene expression triggers formation of the blastoderm epithelium via cellularization and simultaneous division of ~6000 mono-nucleated cells from a single internal yolk cell. During these steps, the cortex is regulated in space and time, gains domain and sub-domain structure, and undergoes mesoscale interactions that lay a structural foundation of animal development.

Physically and Chemically Compartmentalized Polymersomes for Programmed Delivery and Biological Applications

Multicompartment polymersomes (MCPs) refer to polymersomes that not only contain one single compartment, either in the membrane or in the internal cavity, but also mimic the compartmentalized structure of living cells, attracting much attention in programmed delivery and biological applications. The investigation of MCPs may promote the application of soft nanomaterials in biomedicine. This Review seeks to highlight the recent advances of the design principles, synthetic strategies, and biomedical applications of MCPs. The compartmentalization types including chemical, physical, and hybrid compartmentalization are discussed. Subsequently, the design and controlled synthesis of MCPs by the self-assembly of amphiphilic polymers, double emulsification, coprecipitation, microfluidics and particle assembly, etc. are summarized. Furthermore, the diverse applications of MCPs in programmed delivery of various cargoes and biological applications including cancer therapy, antimicrobials, and regulation of blood glucose levels are highlighted. Finally, future perspectives of MCPs from the aspects of controlled synthesis and applications are proposed.

A multiscale theory for spreading and migration of adhesion-reinforced mesenchymal cells

We present a chemomechanical whole-cell theory for the spreading and migration dynamics of mesenchymal cells that can actively reinforce their adhesion to an underlying viscoelastic substrate as a function of its stiffness. Our multiscale model couples the adhesion reinforcement effect at the subcellular scale with the nonlinear mechanics of the nucleus-cytoskeletal network complex at the cellular scale to explain the concurrent monotonic area-stiffness and non-monotonic speed-stiffness relationships observed in experiments: we consider that large cell spreading on stiff substrates flattens the nucleus, increasing the viscous drag force on it. The resulting force balance dictates a reduction in the migration speed on stiff substrates. We also reproduce the experimental influence of the substrate viscosity on the cell spreading area and migration speed by elucidating how the viscosity may either maintain adhesion reinforcement or prevent it depending on the substrate stiffness. Additionally, our model captures the experimental directed migration behaviour of the adhesion-reinforced cells along a stiffness gradient, known as durotaxis, as well as up or down a viscosity gradient (viscotaxis or anti-viscotaxis), the cell moving towards an optimal viscosity in either case. Overall, our theory explains the intertwined mechanics of the cell spreading, migration speed and direction in the presence of the molecular adhesion reinforcement mechanism.

Recent advances in nano-scaffolds for tissue engineering applications: Toward natural therapeutics

Among the promising methods for repairing or replacing tissue defects in the human body and the hottest research topics in medical science today are regenerative medicine and tissue engineering. On the other hand, nanotechnology has been expanded into different areas of regenerative medicine and tissue engineering due to its essential benefits in improving performance in various fields. Nanotechnology, a helpful strategy in tissue engineering, offers new solutions to unsolved problems. Especially considering the excellent physicochemical properties of nanoscale structures, their application in regenerative medicine has been gradually developed, and a lot of research has been conducted in this field. In this regard, various nanoscale structures, including nanofibers, nanosheets, nanofilms, nano-clays, hollow spheres, and different nanoparticles, have been developed to advance nanotechnology strategies with tissue repair goals. Here, we comprehensively review the application of the mentioned nanostructures in constructing nanocomposite scaffolds for regenerative medicine and tissue engineering. This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Implantable Materials and Surgical Technologies > Nanotechnology in Tissue Repair and Replacement Diagnostic Tools > Biosensing.

Systems Biology and Cytokines Potential Role in Lung Cancer Immunotherapy Targeting Autophagic Axis

Lung cancer accounts for the highest number of deaths among men and women worldwide. Although extensive therapies, either alone or in conjunction with some specific drugs, continue to be the principal regimen for evolving lung cancer, significant improvements are still needed to understand the inherent biology behind progressive inflammation and its detection. Unfortunately, despite every advancement in its treatment, lung cancer patients display different growth mechanisms and continue to die at significant rates. Autophagy, which is a physiological defense mechanism, serves to meet the energy demands of nutrient-deprived cancer cells and sustain the tumor cells under stressed conditions. In contrast, autophagy is believed to play a dual role during different stages of tumorigenesis. During early stages, it acts as a tumor suppressor, degrading oncogenic proteins; however, during later stages, autophagy supports tumor cell survival by minimizing stress in the tumor microenvironment. The pivotal role of the IL6-IL17-IL23 signaling axis has been observed to trigger autophagic events in lung cancer patients. Since the obvious roles of autophagy are a result of different immune signaling cascades, systems biology can be an effective tool to understand these interconnections and enhance cancer treatment and immunotherapy. In this review, we focus on how systems biology can be exploited to target autophagic processes that resolve inflammatory responses and contribute to better treatment in carcinogenesis.

Couple stresses and discrete potentials in the vertex model of cellular monolayers

The vertex model is widely used to simulate the mechanical properties of confluent epithelia and other multicellular tissues. This inherently discrete framework allows a Cauchy stress to be attributed to each cell, and its symmetric component has been widely reported, at least for planar monolayers. Here, we consider the stress attributed to the neighbourhood of each tricellular junction, evaluating in particular its leading-order antisymmetric component and the associated couple stresses, which characterise the degree to which individual cells experience (and resist) in-plane bending deformations. We develop discrete potential theory for localised monolayers having disordered internal structure and use this to derive the analogues of Airy and Mindlin stress functions. These scalar potentials typically have broad-banded spectra, highlighting the contributions of small-scale defects and boundary layers to global stress patterns. An affine approximation attributes couple stresses to pressure differences between cells sharing a trijunction, but simulations indicate an additional role for non-affine deformations.

Identification of cancer types from gene expressions using learning techniques

Tumor is the major cause of death all around the world in recent days. Early detection and prediction of a cancer type are important for a patient's well-being. Functional genomic data has recently been used in the effective and early detection of cancer. According to previous research, the use of microarray data in cancer prediction has evidenced two main problems as high dimensionality and limited sample size. Several researchers have used numerous statistical and machine learning-based methods to classify cancer types but still, limitations are there which makes cancer classification a difficult job. Deep Learning (DL) and Convolutional Neural Networks (CNN) have been proven with effective analyses of unstructured data including gene expression data. In the proposed method gene expression data for five types of cancer is collected from The Cancer Genome Atlas (TCGA). Prominent features are selected using a hybrid Particle Swarm Optimization (PSO) and Random Forest (RF) algorithm followed by the use of Principal Component Analysis (PCA) for dimensionality reduction. Finally, for classification blend of Convolutional Neural Network (CNN) and Bi-directional Long Short Term Memory (Bi-LSTM) is used to predict the target type of cancer. Experimental results demonstrate that accuracy of the proposed method is 96.89%. As compared to existing work, our method outperformed with better results.

Generative models of morphogenesis in developmental biology

Understanding the mechanism by which cells coordinate their differentiation and migration is critical to our understanding of many fundamental processes such as wound healing, disease progression, and developmental biology. Mathematical models have been an essential tool for testing and developing our understanding, such as models of cells as soft spherical particles, reaction-diffusion systems that couple cell movement to environmental factors, and multi-scale multi-physics simulations that combine bottom-up rule-based models with continuum laws. However, mathematical models can often be loosely related to data or have so many parameters that model behaviour is weakly constrained. Recent methods in machine learning introduce new means by which models can be derived and deployed. In this review, we discuss examples of mathematical models of aspects of developmental biology, such as cell migration, and how these models can be combined with these recent machine learning methods.

Single-cell mechanical analysis reveals viscoelastic similarities between normal and neoplastic brain cells

Understanding cancer cell mechanics allows for the identification of novel disease mechanisms, diagnostic biomarkers, and targeted therapies. In this study, we utilized our previously established fluid shear stress assay to investigate and compare the viscoelastic properties of normal immortalized human astrocytes (IHAs) and invasive human glioblastoma (GBM) cells when subjected to physiological levels of shear stress that are present in the brain microenvironment. We used a parallel-flow microfluidic shear system and a camera-coupled optical microscope to expose single cells to fluid shear stress and monitor the resulting deformation in real-time, respectively. From the video-rate imaging, we fed cell deformation information from digital image correlation into a three-parameter generalized Maxwell model to quantify the nuclear and cytoplasmic viscoelastic properties of single cells. We further quantified actin cytoskeleton density and alignment in IHAs and GBM cells via immunofluorescence microscopy and image analysis techniques. Results from our study show that contrary to the behavior of many extracranial cells, normal and cancerous brain cells do not exhibit significant differences in their viscoelastic behavior. Moreover, we also found that the viscoelastic properties of the nucleus and cytoplasm as well as the actin cytoskeletal densities of both brain cell types are similar. Our work suggests that malignant GBM cells exhibit unique mechanical behaviors not seen in other cancer cell types. These results warrant future study to elucidate the distinct biophysical characteristics of the brain and reveal novel mechanical attributes of GBM and other primary brain tumors.

From cells to form: A roadmap to study shape emergence in vivo

Organogenesis arises from the collective arrangement of cells into progressively 3D-shaped tissue. The acquisition of a correctly shaped organ is then the result of a complex interplay between molecular cues, responsible for differentiation and patterning, and the mechanical properties of the system, which generate the necessary forces that drive correct shape emergence. Nowadays, technological advances in the fields of microscopy, molecular biology, and computer science are making it possible to see and record such complex interactions in incredible, unforeseen detail within the global context of the developing embryo. A quantitative and interdisciplinary perspective of developmental biology becomes then necessary for a comprehensive understanding of morphogenesis. Here, we provide a roadmap to quantify the events that lead to morphogenesis from imaging to image analysis, quantification, and modeling, focusing on the discrete cellular and tissue shape changes, as well as their mechanical properties.

Transcription factor competition facilitates self-sustained oscillations in single gene genetic circuits

Genetic feedback loops can be used by cells to regulate internal processes or to keep track of time. It is often thought that, for a genetic circuit to display self-sustained oscillations, a degree of cooperativity is needed in the binding and unbinding of actor species. This cooperativity is usually modeled using a Hill function, regardless of the actual promoter architecture. Furthermore, genetic circuits do not operate in isolation and often transcription factors are shared between different promoters. In this work we show how mathematical modelling of genetic feedback loops can be facilitated with a mechanistic fold-change function that takes into account the titration effect caused by competing binding sites for transcription factors. The model shows how the titration effect facilitates self-sustained oscillations in a minimal genetic feedback loop: a gene that produces its own repressor directly without cooperative transcription factor binding. The use of delay-differential equations leads to a stability contour that predicts whether a genetic feedback loop will show self-sustained oscillations, even when taking the bursty nature of transcription into account.

Image-based scatter correction for cone-beam CT using flip swin transformer U-shape network

BACKGROUND

Cone beam computed tomography (CBCT) plays an increasingly important role in image-guided radiation therapy. However, the image quality of CBCT is severely degraded by excessive scatter contamination, especially in the abdominal region, hindering its further applications in radiation therapy.

PURPOSE

To restore low-quality CBCT images contaminated by scatter signals, a scatter correction algorithm combining the advantages of convolutional neural networks (CNN) and Swin Transformer is proposed.

METHODS

In this paper a scatter correction model for CBCT image, the Flip Swin Transformer U-shape network (FSTUNet) model, is proposed. In this model, the advantages of CNN in texture detail and Swin Transformer in global correlation are used to accurately extract shallow and deep features, respectively. Instead of using the original Swin Transformer tandem structure, we build the Flip Swin Transformer Block to achieve a more powerful inter-window association extraction. The validity and clinical relevance of the method is demonstrated through extensive experiments on a Monte Carlo (MC) simulation dataset and frequency split dataset generated by a validated method, respectively.

RESULT

Experimental results on the MC simulated dataset show that the root mean square error of images corrected by the method is reduced from over 100 HU to about 7 HU. Both the structural similarity index measure (SSIM) and the universal quality index (UQI) are close to 1. Experimental results on the frequency split dataset demonstrate that the method not only corrects shading artifacts but also exhibits a high degree of structural consistency. In addition, comparison experiments show that FSTUNet outperforms UNet, Deep Residual Convolutional Neural Network (DRCNN), DSENet, Pix2pixGAN, and 3DUnet methods in both qualitative and quantitative metrics.

CONCLUSIONS

Accurately capturing the features at different levels is greatly beneficial for reconstructing high-quality scatter-free images. The proposed FSTUNet method is an effective solution to CBCT scatter correction and has the potential to improve the accuracy of CBCT image-guided radiation therapy.

Kinesin and myosin motors compete to drive rich multiphase dynamics in programmable cytoskeletal composites

The cellular cytoskeleton relies on diverse populations of motors, filaments, and binding proteins acting in concert to enable nonequilibrium processes ranging from mitosis to chemotaxis. The cytoskeleton's versatile reconfigurability, programmed by interactions between its constituents, makes it a foundational active matter platform. However, current active matter endeavors are limited largely to single force-generating components acting on a single substrate-far from the composite cytoskeleton in cells. Here, we engineer actin-microtubule (MT) composites, driven by kinesin and myosin motors and tuned by crosslinkers, to ballistically restructure and flow with speeds that span three orders of magnitude depending on the composite formulation and time relative to the onset of motor activity. Differential dynamic microscopy analyses reveal that kinesin and myosin compete to delay the onset of acceleration and suppress discrete restructuring events, while passive crosslinking of either actin or MTs has an opposite effect. Our minimal advection-diffusion model and spatial correlation analyses correlate these dynamics to structure, with motor antagonism suppressing reconfiguration and demixing, while crosslinking enhances clustering. Despite the rich formulation space and emergent formulation-dependent structures, the nonequilibrium dynamics across all composites and timescales can be organized into three classes-slow isotropic reorientation, fast directional flow, and multimode restructuring. Moreover, our mathematical model demonstrates that diverse structural motifs can arise simply from the interplay between motor-driven advection and frictional drag. These general features of our platform facilitate applicability to other active matter systems and shed light on diverse ways that cytoskeletal components can cooperate or compete to enable wide-ranging cellular processes.

Configurational entropy is an intrinsic driver of tissue structural heterogeneity

Tissues comprise ordered arrangements of cells that can be surprisingly disordered in their details. How the properties of single cells and their microenvironment contribute to the balance between order and disorder at the tissue-scale remains poorly understood. Here, we address this question using the self-organization of human mammary organoids as a model. We find that organoids behave like a dynamic structural ensemble at the steady state. We apply a maximum entropy formalism to derive the ensemble distribution from three measurable parameters - the degeneracy of structural states, interfacial energy, and tissue activity (the energy associated with positional fluctuations). We link these parameters with the molecular and microenvironmental factors that control them to precisely engineer the ensemble across multiple conditions. Our analysis reveals that the entropy associated with structural degeneracy sets a theoretical limit to tissue order and provides new insight for tissue engineering, development, and our understanding of disease progression.

Heteroprotein complex between soy protein isolate and lysozyme: Protein conformation, lysozyme activity, and structural characterization

Heteroprotein complexes are formed by electrostatic interactions of oppositely charged proteins in a purely aqueous environment. Understanding the relationship between their structural and functional properties will contribute to their tailor-made applications. Therefore, this study investigated the protein conformation, assembling structure, and enzyme activity of soy protein isolate/lysozyme (SPI/LYS) complexes at mass ratios of 2:1 (soluble complex) and 1:1.3 (stoichiometric ratio). Electrostatic complexation increased the surface hydrophobicity of complexes. Their surface hydrophobicity decreased with increasing NaCl concentrations and reached the theoretical values at the critical salt concentration of 200 mM NaCl. Electrostatic complexation did not decrease the LYS activity (∼43,000 units/mg). SPI/LYS complexes exhibited flocculated structures in which the two proteins were unevenly distributed; these were typical amorphous complexes. High dilution disassembled these complexes over 5 μm into particles of ∼100 nm, and NaCl reduced the size of these particles. Immobilized water was detected in the complexes formed by particle flocculation.

Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics

Despite the prevalence of superresolution (SR) microscopy, quantitative live-cell SR imaging that maintains the completeness of delicate structures and the linearity of fluorescence signals remains an uncharted territory. Structured illumination microscopy (SIM) is the ideal tool for live-cell SR imaging. However, it suffers from an out-of-focus background that leads to reconstruction artifacts. Previous post hoc background suppression methods are prone to human bias, fail at densely labeled structures, and are nonlinear. Here, we propose a physical model-based Background Filtering method for living cell SR imaging combined with the 2D-SIM reconstruction procedure (BF-SIM). BF-SIM helps preserve intricate and weak structures down to sub-70 nm resolution while maintaining signal linearity, which allows for the discovery of dynamic actin structures that, to the best of our knowledge, have not been previously monitored.

Direct detection of deformation modes on varying length scales in active biopolymer networks

Correlated flows and forces that emerge from active matter orchestrate complex processes such as shape regulation and deformations in biological cells and tissues. The active materials central to cellular mechanics are cytoskeletal networks, where molecular motor activity drives deformations and remodeling. Here, we investigate deformation modes in actin networks driven by the molecular motor myosin II through quantitative fluorescence microscopy. We examine the deformation anisotropy at different length scales in networks of entangled, cross-linked, and bundled actin. In sparsely cross-linked networks, we find myosin-dependent biaxial buckling modes across length scales. In cross-linked bundled networks, uniaxial contraction is predominate on long length scales, while the uniaxial or biaxial nature of the deformation depends on bundle microstructure at shorter length scales. The anisotropy of deformations may provide insight to regulation of collective behavior in a variety of active materials.

Dense Sampling Approaches for Psychiatry Research: Combining Scanners and Smartphones

Together, data from brain scanners and smartphones have sufficient coverage of biology, psychology, and environment to articulate between-person differences in the interplay within and across biological, psychological, and environmental systems thought to underlie psychopathology. An important next step is to develop frameworks that combine these two modalities in ways that leverage their coverage across layers of human experience to have maximum impact on our understanding and treatment of psychopathology. We review literature published in the last 3 years highlighting how scanners and smartphones have been combined to date, outline and discuss the strengths and weaknesses of existing approaches, and sketch a network science framework heretofore underrepresented in work combining scanners and smartphones that can push forward our understanding of health and disease.

Time-reversal even charge hall effect from twisted interface coupling

Under time-reversal symmetry, a linear charge Hall response is usually deemed to be forbidden by the Onsager relation. In this work, we discover a scenario for realizing a time-reversal even linear charge Hall effect in a non-isolated two-dimensional crystal allowed by time reversal symmetry. The restriction by Onsager relation is lifted by interfacial coupling with an adjacent layer, where the overall chiral symmetry requirement is fulfilled by a twisted stacking. We reveal the underlying band geometric quantity as the momentum-space vorticity of layer current. The effect is demonstrated in twisted bilayer graphene and twisted homobilayer transition metal dichalcogenides with a wide range of twist angles, which exhibit giant Hall ratios under experimentally practical conditions, with gate voltage controlled on-off switch. This work reveals intriguing Hall physics in chiral structures, and opens up a research direction of layertronics that exploits the quantum nature of layer degree of freedom to uncover exciting effects.

Chasing the spin gap through the phase diagram of a frustrated Mott insulator

The quest for entangled spin excitations has stimulated intense research on frustrated magnetic systems. For almost two decades, the triangular-lattice Mott insulator κ-(BEDT-TTF)₂Cu₂(CN)₃ has been one of the hottest candidates for a gapless quantum spin liquid with itinerant spinons. Very recently, however, this scenario was overturned as electron-spin-resonance (ESR) studies unveiled a spin gap, calling for reevaluation of the magnetic ground state. Here we achieve a precise mapping of this spin-gapped phase through the Mott transition by ultrahigh-resolution strain tuning. Our transport experiments reveal a reentrance of charge localization below T^⋆ = 6 K associated with a gap size of 30-50 K. The negative slope of the insulator-metal boundary, dT^⋆/dp < 0, evidences the low-entropy nature of the spin-singlet ground state. By tuning the enigmatic '6K anomaly' through the phase diagram of κ-(BEDT-TTF)₂Cu₂(CN)₃, we identify it as the transition to a valence-bond-solid phase, in agreement with previous thermal expansion and magnetic resonance studies. This spin-gapped insulating state persists at T → 0 until unconventional superconductivity and metallic transport proliferate.

Signature of spin-triplet exciton condensations in LaCoO3 at ultrahigh magnetic fields up to 600 T

Bose-Einstein condensation of electron-hole pairs, exciton condensation, has been effortfully investigated since predicted 60 years ago. Irrefutable evidence has still been lacking due to experimental difficulties in verifying the condensation of the charge neutral and non-magnetic spin-singlet excitons. Whilst, condensation of spin-triplet excitons is a promising frontier because spin supercurrent and spin-Seebeck effects will be observable. A canonical cobaltite LaCoO₃ under very high magnetic fields is a propitious candidate, yet to be verified. Here, we unveil the exotic phase diagram of LaCoO₃ up to 600 T generated using the electromagnetic flux compression method and the state-of-the-art magnetostriction gauge. We found the continuous magnetostriction curves and a bending structure, which suggest the emergence of two distinct spin-triplet exciton condensates. By constructing a phenomenological model, we showed that quantum fluctuations of excitons are crucial for the field-induced successive transitions. The spin-triplet exciton condensation in a cobaltite, which is three-dimensional and thermally equilibrated, opens up a novel venue for spintronics technologies with spin-supercurrent such as a spin Josephson junction.

Light-driven peristaltic pumping by an actuating splay-bend strip

Despite spectacular progress in microfluidics, small-scale liquid manipulation, with few exceptions, is still driven by external pumps and controlled by large-scale valves, increasing cost and size and limiting complexity. By contrast, optofluidics uses light to power, control and monitor liquid manipulation, potentially allowing for small, self-contained microfluidic devices. Here we demonstrate a soft light-propelled actuator made of liquid crystal gel that pumps microlitre volumes of water. The strip of actuating material serves as both a pump and a channel leading to an extremely simple microfluidic architecture that is both powered and controlled by light. The performance of the pump is well explained by a simple theoretical model in which the light-induced bending of the actuator competes with the liquid's surface tension. The theory highlights that effective pumping requires a threshold light intensity and strip width. The proposed system explores the benefits of shifting the complexity of microfluidic systems from the fabricated device to spatio-temporal control over stimulating light patterns.

The fitness value of ecological information in a variable world

Information processing is increasingly recognized as a fundamental component of life in variable environments, including the evolved use of environmental cues, biomolecular networks, and social learning. Despite this, ecology lacks a quantitative framework for understanding how population, community, and ecosystem dynamics depend on information processing. Here, we review the rationale and evidence for 'fitness value of information' (FVOI), and synthesize theoretical work in ecology, information theory, and probability behind this general mathematical framework. The FVOI quantifies how species' per capita population growth rates can depend on the use of information in their environment. FVOI is a breakthrough approach to linking information processing and ecological and evolutionary outcomes in a changing environment, addressing longstanding questions about how information mediates the effects of environmental change and species interactions.

Viscosity Factor (VF) Complementary to the Statistical Indicators Associated with the Rheological Behavior of Aqueous Solutions of Polyvinyl Alcohol

The rheological behavior of aqueous solutions of polyvinyl alcohol at 4, 6, 8 and 10% by weight has been studied and evaluated at temperatures of 20, 25, 30 and 35 °C, using five non-Newtonian fluid models independent of time: Ferrys, Robertson-Stiff, Williamson, Sisko, and Ellis de Haven. The classical method consists in carrying out regression analysis. Using a comparative procedure of determination coefficients and variances, the model that most appropriately adjusts the experimental data to said model is selected. From the statistical point of view, the Sisko and Robertson-Stiff models present better regression parameters; to better specify the choice of the respective rheological model, a new factor has been proposed in the literature, the viscosity factor (VF), which expresses the relationship between apparent and dynamic viscosity. The analysis of this factor for the five models confirms the greater stability of the Ellis de Haven model in terms of the coefficient of variation of the VF. The value of VF fluctuates between 1 and 2 for all ranges of temperature and concentration experienced for vinyl alcohol solutions. As a consequence of the above, for the choice of the non-Newtonian fluid model associated with the rheology of the aqueous solution of polyvinyl alcohol, it is necessary to analyze the statistical parameters and the VF factor simultaneously.

Bootstrap Embedding on a Quantum Computer

We extend molecular bootstrap embedding to make it appropriate for implementation on a quantum computer. This enables solution of the electronic structure problem of a large molecule as an optimization problem for a composite Lagrangian governing fragments of the total system, in such a way that fragment solutions can harness the capabilities of quantum computers. By employing state-of-art quantum subroutines including the quantum SWAP test and quantum amplitude amplification, we show how a quadratic speedup can be obtained over the classical algorithm, in principle. Utilization of quantum computation also allows the algorithm to match─at little additional computational cost─full density matrices at fragment boundaries, instead of being limited to 1-RDMs. Current quantum computers are small, but quantum bootstrap embedding provides a potentially generalizable strategy for harnessing such small machines through quantum fragment matching.

Thermoresponsive and co-nonsolvency behavior of poly(N-vinyl isobutyramide) and poly(N-isopropyl methacrylamide) as poly(N-isopropyl acrylamide) analogs in aqueous media

Sets of the nonionic polymers poly(N-vinyl isobutyramide) (pNVIBAm) and poly(N-isopropyl methacrylamide) (pNIPMAm) are synthesized by radical polymerization covering the molar mass range from about 20,000 to 150,000 kg mol−1, and their thermoresponsive and solvent-responsive behaviors in aqueous solution are studied. Both polymers feature a lower critical solution temperature (LCST) apparently of the rare so-called type II, as characteristic for their well-studied analogue poly(N-isopropyl acrylamide) (pNIPAm). Moreover, in analogy to pNIPAm, both polymers exhibit co-nonsolvency behavior in mixtures of water with several co-solvents, including short-chain alcohols as well as a range of polar aprotic solvents. While the cloud points of the aqueous solutions are a few degrees higher than those for pNIPAm and increase in the order pNIPAm < pNVIBAm < pNIPMAm, the co-nonsolvency behavior becomes less pronounced in the order pNIPAm > pNVIBAm > pNIPMAm. Exceptionally, pNIPMAm does not show co-nonsolvency in mixtures of water and N,N-dimethylformamide.

Graphical Abstract

Magnetization reversal of perpendicular magnetic anisotropy regulated by ferroelectric polarization in CoFe3N/BaTiO3 heterostructures: first-principles calculations

Exploring the electric-field switching of perpendicular magnetic anisotropy (PMA) in multiferroic heterostructures has important physical significance, which attracts great interest due to its promising application for energy-efficient information storage. Herewith, we investigate the effect of ferroelectric polarization on magnetic anisotropy in CoFe₃N/BaTiO₃ heterostructures using first-principles calculations. The calculations reveal that the magnetic anisotropy of CoFe₃N can be regulated by ferroelectric polarization of BaTiO₃. When the ferroelectric polarization reverses, the PMA of FeCo-TiO₂ and FeN-BaO configurations remains, but in the FeN-TiO₂ and FeCo-BaO cases, magnetic anisotropy inverses between out-of-plane and in-plane direction. Further orbital-resolved analysis indicates that the transition of magnetic anisotropy is mainly attributed to the orbital hybridization of interfacial Fe/Co atoms with O atoms induced by the magnetoelectric effect. This study may open an effective approach toward modulating PMA and lays a foundation to the development of low energy consumption memory devices.

An Updated Review on Advances in Hydrogel-Based Nanoparticles for Liver Cancer Treatment

More than 90% of all liver malignancies are hepatocellular carcinomas (HCCs), for which chemotherapy and immunotherapy are the ideal therapeutic choices. Hepatocellular carcinoma is descended from other liver diseases, such as viral hepatitis, alcoholism, and metabolic syndrome. Normal cells and tissues may suffer damage from common forms of chemotherapy. In contrast to systemic chemotherapy, localized chemotherapy can reduce side effects by delivering a steady stream of chemotherapeutic drugs directly to the tumor site. This highlights the significance of controlled-release biodegradable hydrogels as drug delivery methods for chemotherapeutics. This review discusses using hydrogels as drug delivery systems for HCC and covers thermosensitive, pH-sensitive, photosensitive, dual-sensitive, and glutathione-responsive hydrogels. Compared to conventional systemic chemotherapy, hydrogel-based drug delivery methods are more effective in treating cancer.

Physiological Rhythms and Biological Variation of Biomolecules: The Road to Personalized Laboratory Medicine

The concentration of biomolecules in living systems shows numerous systematic and random variations. Systematic variations can be classified based on the frequency of variations as ultradian (<24 h), circadian (approximately 24 h), and infradian (>24 h), which are partly predictable. Random biological variations are known as between-subject biological variations that are the variations among the set points of an analyte from different individuals and within-subject biological variation, which is the variation of the analyte around individuals’ set points. The random biological variation cannot be predicted but can be estimated using appropriate measurement and statistical procedures. Physiological rhythms and random biological variation of the analytes could be considered the essential elements of predictive, preventive, and particularly personalized laboratory medicine. This systematic review aims to summarize research that have been done about the types of physiological rhythms, biological variations, and their effects on laboratory tests. We have searched the PubMed and Web of Science databases for biological variation and physiological rhythm articles in English without time restrictions with the terms “Biological variation, Within-subject biological variation, Between-subject biological variation, Physiological rhythms, Ultradian rhythms, Circadian rhythm, Infradian rhythms”. It was concluded that, for effective management of predicting, preventing, and personalizing medicine, which is based on the safe and valid interpretation of patients’ laboratory test results, both physiological rhythms and biological variation of the measurands should be considered simultaneously.