Extrinsic hydrophobicity-controlled silver nanoparticles as efficient and stable catalysts for CO2 electrolysis

To realize economically feasible electrochemical CO2 conversion, achieving a high partial current density for value-added products is particularly vital. However, acceleration of the hydrogen evolution reaction due to cathode flooding in a high-current-density region makes this challenging. Herein, we find that partially ligand-derived Ag nanoparticles (Ag-NPs) could prevent electrolyte flooding while maintaining catalytic activity for CO2 electroreduction. This results in a high Faradaic efficiency for CO (>90%) and high partial current density (298.39 mA cm‒2), even under harsh stability test conditions (3.4 V). The suppressed splitting/detachment of Ag particles, due to the lipid ligand, enhance the uniform hydrophobicity retention of the Ag-NP electrode at high cathodic overpotentials and prevent flooding and current fluctuations. The mass transfer of gaseous CO2 is maintained in the catalytic region of several hundred nanometers, with the smooth formation of a triple phase boundary, which facilitate the occurrence of CO2RR instead of HER. We analyze catalyst degradation and cathode flooding during CO2 electrolysis through identical-location transmission electron microscopy and operando synchrotron-based X-ray computed tomography. This study develops an efficient strategy for designing active and durable electrocatalysts for CO2 electrolysis.

Changes in spatial self-consciousness elicit grid cell-like representation in the entorhinal cortex

Grid cells in the entorhinal cortex (EC) encode an individual's location in space, integrating both environmental and multisensory bodily cues. Notably, body-derived signals are also primary signals for the sense of self. While studies have demonstrated that continuous application of visuo-tactile bodily stimuli can induce perceptual shifts in self-location, it remains unexplored whether these illusory changes suffice to trigger grid cell-like representation (GCLR) within the EC, and how this compares to GCLR during conventional virtual navigation. To address this, we systematically induced illusory drifts in self-location toward controlled directions using visuo-tactile bodily stimulation, while maintaining the subjects' visual viewpoint fixed (absent conventional virtual navigation). Subsequently, we evaluated the corresponding GCLR in the EC through functional MRI analysis. Our results reveal that illusory changes in perceived self-location (independent of changes in environmental navigation cues) can indeed evoke entorhinal GCLR, correlating in strength with the magnitude of perceived self-location, and characterized by similar grid orientation as during conventional virtual navigation in the same virtual room. These data demonstrate that the same grid-like representation is recruited when navigating based on environmental, mainly visual cues, or when experiencing illusory forward drifts in self-location, driven by perceptual multisensory bodily cues.

Distributed quantum sensing of multiple phases with fewer photons

Distributed quantum metrology has drawn intense interest as it outperforms the optimal classical counterparts in estimating multiple distributed parameters. However, most schemes so far have required entangled resources consisting of photon numbers equal to or more than the parameter numbers, which is a fairly demanding requirement as the number of nodes increases. Here, we present a distributed quantum sensing scenario in which quantum-enhanced sensitivity can be achieved with fewer photons than the number of parameters. As an experimental demonstration, using a two-photon entangled state, we estimate four phases distributed 3 km away from the central node, resulting in a 2.2 dB sensitivity enhancement from the standard quantum limit. Our results show that the Heisenberg scaling can be achieved even when using fewer photons than the number of parameters. We believe our scheme will open a pathway to perform large-scale distributed quantum sensing with currently available entangled sources.

Purely self-rectifying memristor-based passive crossbar array for artificial neural network accelerators

Memristor-integrated passive crossbar arrays (CAs) could potentially accelerate neural network (NN) computations, but studies on these devices are limited to software-based simulations owing to their poor reliability. Herein, we propose a self-rectifying memristor-based 1 kb CA as a hardware accelerator for NN computations. We conducted fully hardware-based single-layer NN classification tasks involving the Modified National Institute of Standards and Technology database using the developed passive CA, and achieved 100% classification accuracy for 1500 test sets. We also investigated the influences of the defect-tolerance capability of the CA, impact of the conductance range of the integrated memristors, and presence or absence of selection functionality in the integrated memristors on the image classification tasks. We offer valuable insights into the behavior and performance of CA devices under various conditions and provide evidence of the practicality of memristor-integrated passive CAs as hardware accelerators for NN applications.

Roll-to-plate 0.1-second shear-rolling process at elevated temperature for highly aligned nanopatterns

The shear-rolling process is a promising directed self-assembly method that can produce high-quality sub-10 nm block copolymer line-space patterns cost-effectively and straightforwardly over a large area. This study presents a high temperature (280 °C) and rapid (~0.1 s) shear-rolling process that can achieve a high degree of orientation in a single process while effectively preventing film delamination, that can be applied to large-area continuous processes. By minimizing adhesion, normal forces, and ultimate shear strain of the polydimethylsiloxane pad, shearing was successfully performed without peeling up to 280 °C at which the chain mobility significantly increases. This method can be utilized for various high-χ block copolymers and surface neutralization processes. It enables the creation of block copolymer patterns with a half-pitch as small as 8 nm in a unidirectional way. Moreover, the 0.1-second rapid shear-rolling was successfully performed on long, 3-inch width polyimide flexible films to validate its potential for the roll-to-roll process.

Effective protection of photoreceptors using an inflammation-responsive hydrogel to attenuate outer retinal degeneration

Retinitis pigmentosa (RP) is an outer retinal degenerative disease that can lead to photoreceptor cell death and profound vision loss. Although effective regulation of intraretinal inflammation can slow down the progression of the disease, an efficient anti-inflammatory treatment strategy is still lacking. This study reports the fabrication of a hyaluronic acid-based inflammation-responsive hydrogel (IRH) and its epigenetic regulation effects on retinal degeneration. The injectable IRH was designed to respond to cathepsin overexpression in an inflammatory environment. The epigenetic drug, the enhancer of zeste homolog 2 (EZH2) inhibitors, was loaded into the hydrogel to attenuate inflammatory factors. On-demand anti-inflammatory effects of microglia cells via the drug-loaded IRH were verified in vitro and in vivo retinal degeneration 10 (rd10) mice model. Therefore, our IRH not only reduced intraretinal inflammation but also protected photoreceptors morphologically and functionally. Our results suggest the IRH reported here can be used to considerably delay vision loss caused by RP.

Monolithic 3D integration of 2D materials-based electronics towards ultimate edge computing solutions

Three-dimensional (3D) hetero-integration technology is poised to revolutionize the field of electronics by stacking functional layers vertically, thereby creating novel 3D circuity architectures with high integration density and unparalleled multifunctionality. However, the conventional 3D integration technique involves complex wafer processing and intricate interlayer wiring. Here we demonstrate monolithic 3D integration of two-dimensional, material-based artificial intelligence (AI)-processing hardware with ultimate integrability and multifunctionality. A total of six layers of transistor and memristor arrays were vertically integrated into a 3D nanosystem to perform AI tasks, by peeling and stacking of AI processing layers made from bottom-up synthesized two-dimensional materials. This fully monolithic-3D-integrated AI system substantially reduces processing time, voltage drops, latency and footprint due to its densely packed AI processing layers with dense interlayer connectivity. The successful demonstration of this monolithic-3D-integrated AI system will not only provide a material-level solution for hetero-integration of electronics, but also pave the way for unprecedented multifunctional computing hardware with ultimate parallelism.

Characterizing and controlling infrared phonon anomaly of bilayer graphene in optical-electrical force nanoscopy

We, for the first time, report the nanoscopic imaging study of anomalous infrared (IR) phonon enhancement of bilayer graphene, originated from the charge imbalance between the top and bottom layers, resulting in the enhancement of E1u mode of bilayer graphene near 0.2 eV. We modified the multifrequency atomic force microscope platform to combine photo-induced force microscope with electrostatic/Kelvin probe force microscope constituting a novel hybrid nanoscale optical-electrical force imaging system. This enables to observe a correlation between the IR response, doping level, and topographic information of the graphene layers. Through the nanoscale spectroscopic image measurements, we demonstrate that the charge imbalance at the graphene interface can be controlled by chemical (doping effect via Redox mechanism) and mechanical (triboelectric effect by the doped cantilever) approaches. Moreover, we can also diagnosis the subsurface cracks on the stacked few-layer graphene at nanoscale, by monitoring the strain-induced IR phonon shift. Our approach provides new insights into the development of graphene-based electronic and photonic devices and their potential applications.

Physical Body Orientation Impacts Virtual Navigation Experience and Performance

Most human navigation studies in MRI rely on virtual navigation. However, the necessary supine position in MRI makes it fundamentally different from daily ecological navigation. Nonetheless, until now, no study has assessed whether differences in physical body orientation (BO) affect participants' experienced BO during virtual navigation. Here, combining an immersive virtual reality navigation task with subjective BO measures and implicit behavioral measures, we demonstrate that physical BO (either standing or supine) modulates experienced BO. Also, we show that standing upright BO is preferred during spatial navigation: participants were more likely to experience a standing BO and were better at spatial navigation when standing upright. Importantly, we report that showing a supine virtual agent reduces the conflict between the preferred BO and physical supine BO. Our study provides critical, but missing, information regarding experienced BO during virtual navigation, which should be considered cautiously when designing navigation studies, especially in MRI.

Voltage control of magnetism in Fe3-xGeTe2/In2Se3 van der Waals ferromagnetic/ferroelectric heterostructures

We investigate the voltage control of magnetism in a van der Waals (vdW) heterostructure device consisting of two distinct vdW materials, the ferromagnetic Fe3-xGeTe2 and the ferroelectric In2Se3. It is observed that gate voltages applied to the Fe3-xGeTe2/In2Se3 heterostructure device modulate the magnetic properties of Fe3-xGeTe2 with significant decrease in coercive field for both positive and negative voltages. Raman spectroscopy on the heterostructure device shows voltage-dependent increase in the in-plane In2Se3 and Fe3-xGeTe2 lattice constants for both voltage polarities. Thus, the voltage-dependent decrease in the Fe3-xGeTe2 coercive field, regardless of the gate voltage polarity, can be attributed to the presence of in-plane tensile strain. This is supported by density functional theory calculations showing tensile-strain-induced reduction of the magnetocrystalline anisotropy, which in turn decreases the coercive field. Our results demonstrate an effective method to realize low-power voltage-controlled vdW spintronic devices utilizing the magnetoelectric effect in vdW ferromagnetic/ferroelectric heterostructures.

Dual-light emitting 3D encryption with printable fluorescent-phosphorescent metal-organic frameworks

Optical encryption technologies based on room-temperature light-emitting materials are of considerable interest. Herein, we present three-dimensional (3D) printable dual-light-emitting materials for high-performance optical pattern encryption. These are based on fluorescent perovskite nanocrystals (NCs) embedded in metal-organic frameworks (MOFs) designed for phosphorescent host-guest interactions. Notably, perovskite-containing MOFs emit a highly efficient blue phosphorescence, and perovskite NCs embedded in the MOFs emit characteristic green or red fluorescence under ultraviolet (UV) irradiation. Such dual-light-emitting MOFs with independent fluorescence and phosphorescence emissions are employed in pochoir pattern encryption, wherein actual information with transient phosphorescence is efficiently concealed behind fake information with fluorescence under UV exposure. Moreover, a 3D cubic skeleton is developed with the dual-light-emitting MOF powder dispersed in 3D-printable polymer filaments for 3D dual-pattern encryption. This article outlines a universal principle for developing MOF-based room-temperature multi-light-emitting materials and a strategy for multidimensional information encryption with enhanced capacity and security.

Dynamic switching of neural oscillations in the prefrontal-amygdala circuit for naturalistic freeze-or-flight

The medial prefrontal cortex (mPFC) and basolateral amygdala (BLA) are involved in the regulation of defensive behavior under threat, but their engagement in flexible behavior shifts remains unclear. Here, we report the oscillatory activities of mPFC-BLA circuit in reaction to a naturalistic threat, created by a predatory robot in mice. Specifically, we found dynamic frequency tuning among two different theta rhythms (~5 or ~10 Hz) was accompanied by agile changes of two different defensive behaviors (freeze-or-flight). By analyzing flight trajectories, we also found that high beta (~30 Hz) is engaged in the top-down process for goal-directed flights and accompanied by a reduction in fast gamma (60 to 120 Hz, peak near 70 Hz). The elevated beta nested the fast gamma activity by its phase more strongly. Our results suggest that the mPFC-BLA circuit has a potential role in oscillatory gear shifting allowing flexible information routing for behavior switches.

Grasping through dynamic weaving with entangled closed loops

Pick-and-place is essential in diverse robotic applications for industries including manufacturing, and assembly. Soft grippers offer a cost-effective, and low-maintenance alternative for secure object grasping without complex sensing and control systems. However, their inherent softness normally limits payload capabilities and robustness to external disturbances, constraining their applications and hindering reliable performance. In this study, we propose a weaving-inspired grasping mechanism that substantially increases payload capacity while maintaining the use of soft and flexible materials. Drawing from weaving principles, we designed a flexible continuum structure featuring multiple closed-loop strips and employing a kirigami-inspired approach to enable the instantaneous and reversible creation of a woven configuration. The mechanical stability of the woven configuration offers exceptional loading capacity, while the softness of the gripper material ensures safe and adaptive interactions with objects. Experimental results show that the 130 g·f gripper can support up to 100 kg·f. Outperforming competitors in similar weight and softness domains, this breakthrough, enabled by the weaving principle, will broaden the scope of gripper applications to previously inaccessible or barely accessible fields, such as agriculture and logistics.

Autophagy mediates an amplification loop during ferroptosis

Ferroptosis, a programmed cell death, has been identified and associated with cancer and various other diseases. Ferroptosis is defined as a reactive oxygen species (ROS)-dependent cell death related to iron accumulation and lipid peroxidation, which is different from apoptosis, necrosis, autophagy, and other forms of cell death. However, accumulating evidence has revealed a link between autophagy and ferroptosis at the molecular level and has suggested that autophagy is involved in regulating the accumulation of iron-dependent lipid peroxidation and ROS during ferroptosis. Understanding the roles and pathophysiological processes of autophagy during ferroptosis may provide effective strategies for the treatment of ferroptosis-related diseases. In this review, we summarize the current knowledge regarding the regulatory mechanisms underlying ferroptosis, including iron and lipid metabolism, and its association with the autophagy pathway. In addition, we discuss the contribution of autophagy to ferroptosis and elucidate the role of autophagy as a ferroptosis enhancer during ROS-dependent ferroptosis.

A neural probe for concurrent real-time measurement of multiple neurochemicals with electrophysiology in multiple brain regions in vivo

Real-time monitoring of various neurochemicals with high spatial resolution in multiple brain regions in vivo can elucidate neural circuits related to various brain diseases. However, previous systems for monitoring neurochemicals have limitations in observing multiple neurochemicals without crosstalk in real time, and these methods cannot record electrical activity, which is essential for investigating neural circuits. Here, we present a real-time bimodal (RTBM) neural probe that uses monolithically integrated biosensors and multiple shanks to study the connectivity of neural circuits by measuring multiple neurochemicals and electrical neural activity in real time. Using the RTBM probe, we demonstrate concurrent measurements of four neurochemicals-glucose, lactate, choline, and glutamate without cross-talking each other-and electrical activity in real time in vivo. Additionally, we show the functional connectivity between the medial prefrontal cortex and mediodorsal thalamus through the simultaneous measurement of chemical and electrical signals. We expect that our device will contribute to not only elucidating the role of neurochemicals in neural circuits related to brain functions but also developing drugs for various brain diseases related to neurochemicals.

A dorsomedial prefrontal cortex-based dynamic functional connectivity model of rumination

Rumination is a cognitive style characterized by repetitive thoughts about one's negative internal states and is a common symptom of depression. Previous studies have linked trait rumination to alterations in the default mode network, but predictive brain markers of rumination are lacking. Here, we adopt a predictive modeling approach to develop a neuroimaging marker of rumination based on the variance of dynamic resting-state functional connectivity and test it across 5 diverse subclinical and clinical samples (total n = 288). A whole-brain marker based on dynamic connectivity with the dorsomedial prefrontal cortex (dmPFC) emerges as generalizable across the subclinical datasets. A refined marker consisting of the most important features from a virtual lesion analysis further predicts depression scores of adults with major depressive disorder (n = 35). This study highlights the role of the dmPFC in trait rumination and provides a dynamic functional connectivity marker for rumination.

Effective dose window for containing tumor burden under tolerable level

A maximum-tolerated dose (MTD) reduces the drug-sensitive cell population, though it may result in the competitive release of drug resistance. Alternative treatment strategies such as adaptive therapy (AT) or dose modulation aim to impose competitive stress on drug-resistant cell populations by maintaining a sufficient number of drug-sensitive cells. However, given the heterogeneous treatment response and tolerable tumor burden level of individual patients, determining an effective dose that can fine-tune competitive stress remains challenging. This study presents a mathematical model-driven approach that determines the plausible existence of an effective dose window (EDW) as a range of doses that conserve sufficient sensitive cells while maintaining the tumor volume below a threshold tolerable tumor volume (TTV). We use a mathematical model that explains intratumor cell competition. Analyzing the model, we derive an EDW determined by TTV and the competitive strength. By applying a fixed endpoint optimal control model, we determine the minimal dose to contain cancer at a TTV. As a proof of concept, we study the existence of EDW for a small cohort of melanoma patients by fitting the model to longitudinal tumor response data. We performed identifiability analysis, and for the patients with uniquely identifiable parameters, we deduced patient-specific EDW and minimal dose. The tumor volume for a patient could be theoretically contained at the TTV either using continuous dose or AT strategy with doses belonging to EDW. Further, we conclude that the lower bound of the EDW approximates the minimum effective dose (MED) for containing tumor volume at the TTV.

Developmental timing-dependent organization of synaptic connections between mossy fibers and granule cells in the cerebellum

The long-standing hypothesis that synapses between mossy fibers (MFs) and cerebellar granule cells (GCs) are organized according to the origins of MFs and locations of GC axons, parallel fibers (PFs), is supported by recent findings. However, the mechanisms of such organized synaptic connections remain unknown. Here, using our technique that enabled PF location-dependent labeling of GCs in mice, we confirmed that synaptic connections of GCs with specific MFs originating from the pontine nucleus (PN-MFs) and dorsal column nuclei (DCoN-MFs) were gently but differentially organized according to their PF locations. We then found that overall MF-GC synaptic connectivity was biased in a way that dendrites of GCs having nearby PFs tended to connect with the same MF terminals, implying that the MF origin- and PF location-dependent organization is associated with the overall biased MF-GC synaptic connectivity. Furthermore, the development of PN-MFs preceded that of DCoN-MFs, which matches the developmental sequence of GCs that preferentially connect with each type of these MFs. Thus, our results revealed that overall MF-GC synaptic connectivity is biased in terms of PF locations, and suggested that such connectivity is likely the result of synaptic formation between developmental timing-matched partners.

Quantum enhanced multiple-phase estimation with multi-mode N00N states

Quantum metrology can achieve enhanced sensitivity for estimating unknown parameters beyond the standard quantum limit. Recently, multiple-phase estimation exploiting quantum resources has attracted intensive interest for its applications in quantum imaging and sensor networks. For multiple-phase estimation, the amount of enhanced sensitivity is dependent on quantum probe states, and multi-mode N00N states are known to be a key resource for this. However, its experimental demonstration has been missing so far since generating such states is highly challenging. Here, we report generation of multi-mode N00N states and experimental demonstration of quantum enhanced multiple-phase estimation using the multi-mode N00N states. In particular, we show that the quantum Cramer-Rao bound can be saturated using our two-photon four-mode N00N state and measurement scheme using a 4 × 4 multi-mode beam splitter. Our multiple-phase estimation strategy provides a faithful platform to investigate multiple parameter estimation scenarios.

Scalable recombinase-based gene expression cascades

Temporal modulation of the expression of multiple genes underlies complex complex biological phenomena. However, there are few scalable and generalizable gene circuit architectures for the programming of sequential genetic perturbations. Here, we describe a modular recombinase-based gene circuit architecture, comprising tandem gene perturbation cassettes (GPCs), that enables the sequential expression of multiple genes in a defined temporal order by alternating treatment with just two orthogonal ligands. We use tandem GPCs to sequentially express single-guide RNAs to encode transcriptional cascades that trigger the sequential accumulation of mutations. We build an all-in-one gene circuit that sequentially edits genomic loci, synchronizes cells at a specific stage within a gene expression cascade, and deletes itself for safety. Tandem GPCs offer a multi-tiered cellular programming tool for modeling multi-stage genetic changes, such as tumorigenesis and cellular differentiation.

Tailoring photosensitive ROS for advanced photodynamic therapy

Photodynamic therapy (PDT) has been considered a noninvasive and cost-effective modality for tumor treatment. However, the complexity of tumor microenvironments poses challenges to the implementation of traditional PDT. Here, we review recent advances in PDT to resolve the current problems. Major breakthroughs in PDTs are enabling significant progress in molecular medicine and are interconnected with innovative strategies based on smart bio/nanomaterials or therapeutic insights. We focus on newly developed PDT strategies designed by tailoring photosensitive reactive oxygen species generation, which include the use of proteinaceous photosensitizers, self-illumination, or oxygen-independent approaches. While these updated PDT platforms are expected to enable major advances in cancer treatment, addressing future challenges related to biosafety and target specificity is discussed throughout as a necessary goal to expand the usefulness of PDT.

Selective electrochemical reduction of nitric oxide to hydroxylamine by atomically dispersed iron catalyst

Electrocatalytic conversion of nitrogen oxides to value-added chemicals is a promising strategy for mitigating the human-caused unbalance of the global nitrogen-cycle, but controlling product selectivity remains a great challenge. Here we show iron-nitrogen-doped carbon as an efficient and durable electrocatalyst for selective nitric oxide reduction into hydroxylamine. Using in operando spectroscopic techniques, the catalytic site is identified as isolated ferrous moieties, at which the rate for hydroxylamine production increases in a super-Nernstian way upon pH decrease. Computational multiscale modelling attributes the origin of unconventional pH dependence to the redox active (non-innocent) property of NO. This makes the rate-limiting NO adsorbate state more sensitive to surface charge which varies with the pH-dependent overpotential. Guided by these fundamental insights, we achieve a Faradaic efficiency of 71% and an unprecedented production rate of 215 μmol cm-2 h-1 at a short-circuit mode in a flow-type fuel cell without significant catalytic deactivation over 50 h operation.

3D high-density microelectrode array with optical stimulation and drug delivery for investigating neural circuit dynamics

Investigation of neural circuit dynamics is crucial for deciphering the functional connections among regions of the brain and understanding the mechanism of brain dysfunction. Despite the advancements of neural circuit models in vitro, technologies for both precisely monitoring and modulating neural activities within three-dimensional (3D) neural circuit models have yet to be developed. Specifically, no existing 3D microelectrode arrays (MEAs) have integrated capabilities to stimulate surrounding neurons and to monitor the temporal evolution of the formation of a neural network in real time. Herein, we present a 3D high-density multifunctional MEA with optical stimulation and drug delivery for investigating neural circuit dynamics within engineered 3D neural tissues. We demonstrate precise measurements of synaptic latencies in 3D neural networks. We expect our 3D multifunctional MEA to open up opportunities for studies of neural circuits through precise, in vitro investigations of neural circuit dynamics with 3D brain models.

Asymmetric optical camouflage: tuneable reflective colour accompanied by the optical Janus effect

Going beyond an improved colour gamut, an asymmetric colour contrast, which depends on the viewing direction, and its ability to readily deliver information could create opportunities for a wide range of applications, such as next-generation optical switches, colour displays, and security features in anti-counterfeiting devices. Here, we propose a simple Fabry-Perot etalon architecture capable of generating viewing-direction-sensitive colour contrasts and encrypting pre-inscribed information upon immersion in particular solvents (optical camouflage). Based on the experimental verification of the theoretical modelling, we have discovered a completely new and exotic optical phenomenon involving a tuneable colour switch for viewing-direction-dependent information delivery, which we define as asymmetric optical camouflage.

3'-Sialyllactose prebiotics prevents skin inflammation via regulatory T cell differentiation in atopic dermatitis mouse models

3'-Sialyllactose (3'-SL), a natural prebiotic, maintains immune homeostasis and exerts anti-inflammatory and anti-arthritic effects. Although regulatory T cells (Tregs) prevent excessive inflammation and maintain immune tolerance, the effect of 3'-SL on Treg regulation is unclear. This study aimed to investigate the effect of 3'-SL on Treg responses in atopic dermatitis (AD) pathogenesis. Oral administration of 3'-SL reduced AD-like symptoms such as ear, epidermal, and dermal thickness in repeated topical application of house dust mites (HDM) and 2,4-dinitrochlorobenzene (DNCB). 3'-SL inhibited IgE, IL-1β, IL-6, and TNF-α secretion and markedly downregulated AD-related cytokines including IL-4, IL-5, IL-6, IL-13, IL-17, IFN-γ, TNF-α, and Tslp through regulation of NF-κB in ear tissue. Additionally, in vitro assessment of Treg differentiation revealed that 3'-SL directly induced TGF-β-mediated Treg differentiation. Furthermore, 3'-SL administration also ameliorated sensitization and elicitation of AD pathogenesis by suppressing mast cell infiltration and production of IgE and pro-inflammatory cytokines in mouse serum by mediating the Treg response. Furthermore, Bifidobacterium population was also increased by 3'-SL administration as prebiotics. Our data collectively show that 3'-SL has therapeutic effects against AD progression by inducing Treg differentiation, downregulating AD-related cytokines, and increasing the Bifidobacterium population.

Metal-organic framework-derived metal oxide nanoparticles@reduced graphene oxide composites as cathode materials for rechargeable aluminium-ion batteries

The use of metal oxides as electrode materials has seen great success in lithium-ion batteries. However, this type of electrode materials has been regarded as an improper option for rechargeable aluminium-ion batteries (AIBs) in comparison with sulfides and selenides, and has, thus, been nearly abandoned. Here, we demonstrate the suitability of metal oxides as cathode materials of AIBs, exhibiting high electrochemical activities toward Al-ion storage. We designed economical metal-oxide cathodes (Co3O4@reduced graphene oxide (rGO), Fe2O3@rGO, and CoFe2O4@rGO) for AIBs. The Co3O4@rGO displayed superior electrochemical properties, regarding both capacity and lifespan, to the current state-of-the-art cathode material reported by scientific literature. Furthermore, the CoFe2O4@rGO exhibits rational electrochemical capacities and an extremely stable charge/discharge process with an excellent Coulombic efficiency of 99.6%. The proposed study expects to stimulate researchers to focus on the overlooked metal oxides as competitive cathode materials for high performance AIBs.

Two-dimensional boron nitride as a sulfur fixer for high performance rechargeable aluminum-sulfur batteries

Aluminum-ion batteries (AIBs) are regarded as promising candidates for post-lithium-ion batteries due to their lack of flammability and electrochemical performance comparable to other metal-ion batteries. The lack of suitable cathode materials, however, has hindered the development of high-performing AIBs. Sulfur is a cost-efficient material, having distinguished electrochemical properties, and is considered an attractive cathode material for AIBs. Several pioneering reports have shown that aluminum-sulfur batteries (ASBs) exhibit superior electrochemical capacity over other cathode materials for AIBs. However, a rapid decay in the capacity is a huge barrier for their practical applications. Here, we have demonstrated systematically for the first time that the two-dimensional layered materials (e.g. MoS2, WS2, and BN) can serve as fixers of S and sulfide compounds during repeated charge/discharge processes; BN/S/C displays the highest capacity of 532 mAh g-1 (at a current density of 100 mA g-1) compared with the current state-of-the-art cathode material for AIBs. Further, we could improve the life-span of ASBs to an unprecedented 300 cycles with a high Coulombic efficiency of 94.3%; discharge plateaus at ~1.15 V vs. AlCl4-/Al was clearly observed during repeated charge/discharge cycling. We believe that this work opens up a new method for achieving high-performing ASBs.

Universal perpendicular orientation of block copolymer microdomains using a filtered plasma

Sub-10 nm patterns prepared by directed self-assembly (DSA) of block copolymer (BCP) thin films offer a breakthrough method to overcome the limitations of photolithography. Perpendicular orientation of the BCP nanostructures is essential for lithographic applications, but dissimilar surface/interfacial energies of two blocks generally favour parallel orientations, so that the perpendicular orientation could only be obtained under very limited conditions. Here, we introduce a generalized method for creating perpendicular orientations by filtered plasma treatment of the BCP films. By cross-linking the surface of disordered BCP films using only physical collisions of neutral species without ion bombardment or UV irradiation, neutral layers consistent with the BCP volume fraction are produced that promote the perpendicular orientations. This method works with BCPs of various types, volume fractions, and molecular weights individually at the top and bottom interfaces, so it was applied to orientation-controlled 3D multilayer structures and DSA processes for sub-10 nm line-spacing patterns.

Dentate granule and mossy cells exhibit distinct spatiotemporal responses to local change in a one-dimensional landscape of visual-tactile cues

The dentate gyrus (DG) is critical for detecting changes in environments; however, how granule cells (GCs) and mossy cells (MCs), the two excitatory cell types of the DG, respond to small changes in the object layout is unclear. Here, we recorded GCs and MCs, identified by spike feature and optogenetic tagging, as mice ran on a treadmill belt enriched with visual-tactile cues. We observed that fixing a new cue on the belt induced a reconfiguration of GC and MC spatial representations via the emergence, extinction and rate alteration of firing fields. For both GCs and MCs, the response was maximal near the cue and spread over the entire belt. However, compared to the GC response, the MC response was stronger and more immediate, peaked at a slightly earlier belt position, and exhibited a transient component reminiscent of neuromodulatory activity. A competitive neural network model reproduced the GC response contingent on both the introduction of new object-vector inputs and the reconfiguration of MC activity, the former being critical for spreading the GC response in locations distant from the cue. These findings suggest that GCs operate as a competitive network and that MCs precede GCs in detecting changes and help expand the range of GC pattern separation.

Pattern Learning Electronic Density of States

Electronic density of states (DOS) is a key factor in condensed matter physics and material science that determines the properties of metals. First-principles density-functional theory (DFT) calculations have typically been used to obtain the DOS despite the considerable computation cost. Herein, we report a fast machine learning method for predicting the DOS patterns of not only bulk structures but also surface structures in multi-component alloy systems by a principal component analysis. Within this framework, we use only four features to define the composition, atomic structure, and surfaces of alloys, which are the d-orbital occupation ratio, coordination number, mixing factor, and the inverse of miller indices. While the DFT method scales as O(N3) in which N is the number of electrons in the system size, our pattern learning method can be independent on the number of electrons. Furthermore, our method provides a pattern similarity of 91 ~ 98% compared to DFT calculations. This reveals that our learning method will be an alternative that can break the trade-off relationship between accuracy and speed that is well known in the field of electronic structure calculations.

Effect of chain flexibility on cell adhesion: Semi-flexible model-based analysis of cell adhesion to hydrogels

Hydrogels have been developed and applied to various biomedical applications due to their biocompatibility. However, understanding of modulation between cells to hydrogel interface is still unclear, and parameters to explain the interaction are not sophisticated enough. In this report, we studied the effect of polymer chain flexibility on cell adhesion to various hydrogel constructs of collagen and fibrin gels. Specifically, novel method of semi-flexible model-based analysis confirmed that chain flexibility mediated microstructure of the hydrogels is a critical factor for cell adhesion on their surfaces. The proposed analysis showed possibility of more accurate prediction of biocompatibility of hydrogels, and it should be considered as one of the important criteria for polymer design and selections for enhancing both biocompatibility and biofunctionality.