Liver regeneration after injury is normally mediated by proliferation of hepatocytes, although recent studies have suggested biliary epithelial cells (BECs) can differentiate into hepatocytes during ...severe liver injury when hepatocyte proliferation is impaired. We investigated the effect of hepatocyte‐specific β‐catenin deletion in recovery from severe liver injury and BEC‐to‐hepatocyte differentiation. To induce liver injury, we administered choline‐deficient, ethionine‐supplemented (CDE) diet to three different mouse models, the first being mice with deletion of β‐catenin in both BECs and hepatocytes (Albumin‐Cre; Ctnnb1flox/flox mice). In our second model, we performed hepatocyte lineage tracing by injecting Ctnnb1flox/flox; Rosa‐stopflox/flox‐EYFP mice with the adeno‐associated virus serotype 8 encoding Cre recombinase under the control of the thyroid binding globulin promoter, a virus that infects only hepatocytes. Finally, we performed BEC lineage tracing via Krt19‐CreERT; Rosa‐stopflox/flox‐tdTomato mice. To observe BEC‐to‐hepatocyte differentiation, mice were allowed to recover on normal diet following CDE diet–induced liver injury. Livers were collected from all mice and analyzed by quantitative real‐time polymerase chain reaction, western blotting, immunohistochemistry, and immunofluorescence. We show that mice with lack of β‐catenin in hepatocytes placed on the CDE diet develop severe liver injury with impaired hepatocyte proliferation, creating a stimulus for BECs to differentiate into hepatocytes. In particular, we use both hepatocyte and BEC lineage tracing to show that BECs differentiate into hepatocytes, which go on to repopulate the liver during long‐term recovery. Conclusion: β‐catenin is important for liver regeneration after CDE diet–induced liver injury, and BEC‐derived hepatocytes can permanently incorporate into the liver parenchyma to mediate liver regeneration.
The Tsallis entropy is a useful one-parameter generalization to the standard von Neumann entropy in quantum information theory. In this work, we study the variance of the Tsallis entropy of bipartite ...quantum systems in a random pure state. The main result is an exact variance formula of the Tsallis entropy that involves finite sums of some terminating hypergeometric functions. In the special cases of quadratic entropy and small subsystem dimensions, the main result is further simplified to explicit variance expressions. As a byproduct, we find an independent proof of the recently proven variance formula of the von Neumann entropy based on the derived moment relation to the Tsallis entropy.
A nanoscale, solid‐state physically evolving network is experimentally demonstrated, based on the self‐organization of Ag nanoclusters under an electric field. The adaptive nature of the network is ...determined by the collective inputs from multiple terminals and allows the emulation of heterosynaptic plasticity, an important learning rule in biological systems. These effects are universally observed in devices based on different switching materials.
Polymeric hydrogel actuators refer to intelligent stimuli‐responsive hydrogels that could reversibly deform upon the trigger of various external stimuli. They have thus aroused tremendous attention ...and shown promising applications in many fields including soft robots, artificial muscles, valves, and so on. After a brief introduction of the driving forces that contribute to the movement of living creatures, an overview of the design principles and development history of hydrogel actuators is provided, then the diverse anisotropic structures of hydrogel actuators are summarized, presenting the promising applications of hydrogel actuators, and highlighting the development of multifunctional hydrogel actuators. Finally, the existing challenges and future perspectives of this exciting field are discussed.
As one of the most important stimuli‐responsive materials, biomimetic hydrogel actuators have attracted increased attention. Here, the driving forces that contribute to the movement of living creatures are introduced, and the design principles, diverse anisotropic structures, as well as promising applications of hydrogel actuators are summarized. Finally, the challenges and future outlooks of this field are discussed.
Maintaining enough flexibility and satisfied electrochemical performance simultaneously at subzero temperatures is still challengeable for flexible solid supercapacitors. In the present work, by ...adopting an organohydrogel electrolyte and reduced graphene oxide (rGO) films with microvoids serving as electrodes, a supercapacitor, which could be steadily operated down to −60 °C, has been obtained and has shown excellent low-temperature tolerance. The organohydrogel electrolyte consists of LiCl in glycerol/water solution containing polyvinyl alcohol, exhibiting excellent flexibility at −60 °C. Due to the introduction of micropores between rGO sheets, the porous membrane can be folded even in liquid nitrogen. Combining the rGO electrodes with the organohydrogel electrolyte, the maximum voltage of the present supercapacitor could be extended to 2.0 V, and a capacitance of 7.73 F·g–1 at −60 °C could be achieved. After 5000 charge/discharge cycles at −20 °C, the capacitance retention rate is 87.5%. The excellent flexibility and low-temperature resistance of the current supercapacitor pave a novel way for developing compression-resistant electronic samples compatible with a low-temperature environment.
Memristors have been considered as a leading candidate for a number of critical applications ranging from nonvolatile memory to non-Von Neumann computing systems. Feature extraction, which aims to ...transform input data from a high-dimensional space to a space with fewer dimensions, is an important technique widely used in machine learning and pattern recognition applications. Here, we experimentally demonstrate that memristor arrays can be used to perform principal component analysis, one of the most commonly used feature extraction techniques, through online, unsupervised learning. Using Sanger’s rule, that is, the generalized Hebbian algorithm, the principal components were obtained as the memristor conductances in the network after training. The network was then used to analyze sensory data from a standard breast cancer screening database with high classification success rate (97.1%).
Photoactivatable probes, with high-precision spatial and temporal control, have largely advanced bioimaging applications, particularly for fluorescence microscopy. While emerging Raman probes have ...recently pushed the frontiers of Raman microscopy for noninvasive small-molecule imaging and supermultiplex optical imaging with superb sensitivity and specificity, photoactivatable Raman probes remain less explored. Here, we report the first general design of multicolor photoactivatable alkyne Raman probes based on cyclopropenone caging for live-cell imaging and tracking. The fast photochemically generated alkynes from cyclopropenones enable background-free Raman imaging with desired photocontrollable features. We first synthesized and spectroscopically characterized a series of model cyclopropenones and identified the suitable light-activating scaffold. We further engineered the scaffold for enhanced chemical stability in a live-cell environment and improved Raman sensitivity. Organelle-targeting probes were then generated to achieve targeted imaging of mitochondria, lipid droplets, endoplasmic reticulum, and lysosomes. Multiplexed photoactivated imaging and tracking at both subcellular and single-cell levels was next demonstrated to monitor the dynamic migration and interactions of the cellular contents. We envision that this general design of multicolor photoactivatable Raman probes would open up new ways for spatial–temporal controlled profiling and interrogations in complex biological systems with high information throughput.
Visualization of ion transport in electrolytes provides fundamental understandings of electrolyte dynamics and electrolyte-electrode interactions. However, this is challenging because existing ...techniques are hard to capture low ionic concentrations and fast electrolyte dynamics. Here we show that stimulated Raman scattering microscopy offers required resolutions to address a long-lasting question: how does the lithium-ion concentration correlate to uneven lithium deposition? In this study, anions are used to represent lithium ions since their concentrations should not deviate for more than 0.1 mM, even near nanoelectrodes. A three-stage lithium deposition process is uncovered, corresponding to no depletion, partial depletion, and full depletion of lithium ions. Further analysis reveals a feedback mechanism between the lithium dendrite growth and heterogeneity of local ionic concentration, which can be suppressed by artificial solid electrolyte interphase. This study shows that stimulated Raman scattering microscopy is a powerful tool for the materials and energy field.
Memristors have been proposed for a number of applications from nonvolatile memory to neuromorphic systems. Unlike conventional devices based solely on electron transport, memristors operate on the ...principle of resistive switching (RS) based on redistribution of ions. To date, a number of experimental and modeling studies have been reported to probe the RS mechanism; however, a complete physical picture that can quantitatively describe the dynamic RS behavior is still missing. Here, we present a quantitative and accurate dynamic switching model that not only fully accounts for the rich RS behaviors in memristors in a unified framework but also provides critical insight for continued device design, optimization, and applications. The proposed model reveals the roles of electric field, temperature, oxygen vacancy concentration gradient, and different material and device parameters on RS and allows accurate predictions of diverse set/reset, analog switching, and complementary RS behaviors using only material-dependent device parameters.
Dyslipidemia is one of the most important factors for coronary artery disease (CAD). The atherogenic index of plasma (AIP), a new comprehensive lipid index, might be a strong marker for predicting ...the risk of CAD.A hospital-based case-control study including 2936 CAD patients and 2451 controls was conducted in a Chinese population. Traditional lipid parameters were detected, and nontraditional lipid comprehensive indexes were calculated.Compared with controls, CAD patients had higher levels of total cholesterol (TC), triglyceride (TG), and low-density lipoprotein cholesterol (LDL-C). By contrast, the level of high-density lipoprotein cholesterol (HDL-C) was lower in CAD patients. The values of nontraditional lipid profiles, including non-HDL-C, TC/HDL-C, LDL-C/HDL-C, non-HDL-C/HDL-C (atherogenic index, AI), TC*TG*LDL/HDL-C (lipoprotein combine index, LCI), and lg (TG/HDL-C) (AIP), were all significantly higher in the cases than in the controls. The results of Pearson correlation analyses indicated that AIP was positively and significantly correlated with TC (r = 0.125, P < .001), TG (r = 0.810, P < .001), LDL-C (r = 0.035, P < .001), non-HDL-C (r = 0.322, P < .001), TC/HDL-C (r = 0.669, P < .001), LDL-C/HDL-C (r = 0.447, P < .001), AI (r = 0.669, P < .001), and LCI (r = 0.688, P < .001) and was negatively correlated with age (r = -0.122, P < .001) and HDL-C (r = -0.632, P < .001). In the univariate logistic regression analysis, AIP was the lipid parameter that was most strongly associated with CAD, with an unadjusted odds ratio of 1.782 (95% confidence interval: 1.490-2.131, P < .001), for an increase of 1-SD. Multivariate logistic regression analyses revealed that AIP was an independent risk factor for CAD.AIP might be a strong and independent predictor for CAD in the Chinese Han population.
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