In situ Electrical Impedance Tomography for Visualizing Water Transportation in Hygroscopic Aerogels

The global water crisis demands immediate attention, and atmospheric water harvesting (AWH) provides a viable alternative. However, studying the real-time subtle relationship between water absorption, diffusion, and internal structure for hygroscopic materials is challenging. Herein, a dynamic visualization technique is proposed that utilizes an in situ electrical impedance tomography (EIT) system and a precise reconstruction algorithm to achieve real-time monitoring of the water sorption process within aerogels from an internal microstructural perspective. These results can be inferred that composites' pore sizes affecting the kinetics of their moisture absorption. In addition, the diffusion path of moisture absorption and the distribution of stored moisture inside aerogels exhibit intrinsic self-selective behavior, where the fiber skeleton of the aerogel plays a crucial role. In summary, this work proposes a generic EIT-based technique for the in situ and dynamic monitoring of the hygroscopic process, pointing to an entirely new approach regarding research on AWH materials.

Sterically Controlled Synthesis of Amine-Free CsPbBr3 Nanoplatelets for Stable, Pure-Blue Light Emission

Metal halide perovskite nanoplatelets (NPLs) have demonstrated excellent optical properties for light-emitting applications and achieved tunable blue luminescence through thickness control. However, their translation into electronic devices has lagged behind due to poor colloidal and film stability. The main reason for this is the deprotonation of their surface-capped ammonium passivating ligands, resulting in NPL aggregation. Here we report the first facile synthesis of amine-free pure-blue CsPbBr3 NPLs with outstanding thermal and light stability. This is achieved by utilizing an amine-free phosphine oxide route with a surface capping molecule exhibiting large steric hindrance to prevent NPL aggregation. Two-dimensional nuclear magnetic resonance (2D NMR) spectroscopy suggests slower ligand exchange in amine-free NPLs compared to the conventional NPLs, which can be attributed to the strong binding strength of the designated ligand. Consequently, the amine-free NPLs exhibited superior stability against radiation, heat and moisture. We further demonstrate the importance of acid-base equilibrium in this amine-free synthesis route. Through solvent neutralization and passivation with various alkali carbonates, the resulting NPLs attained near-unity photoluminescence quantum yield (PLQY) and pure blue emission.

Regeneration of Thyroid Glands in the Spleen Restores Homeostasis in Thyroidectomy Mice

Surgical removal of the thyroid gland (TG) for treating thyroid disorders leaves the patients on lifelong hormone replacement that partially compensates the physiological needs, but regenerating TG is challenging. Here, an approach is reported to regenerate TG within the spleen for fully restoring the thyroid's functions in mice, by transplanting thyroid tissue blocks to the spleen. Within 48 h, the transplanted tissue efficiently revascularizes, forming thyroid follicles similar to the native gland after 4 weeks. Structurally, the ectopically generated thyroid integrates with the surrounding splenic tissue while maintaining its integrity, separate from the lymphatic tissue. Functionally, it fully restores the native functions of the TG in hormone regulation in response to physiological stimuli, outperforming the established method of oral levothyroxine therapy in maintaining systemic homeostasis. The study demonstrates the full restoration of thyroid functions post-thyroidectomy by intrasplenic TG regeneration, providing fresh insights for designing novel therapies for thyroid-related disorders.

Stepless IR Chromism in Ti3 C2 Tx MXene Tuned by Interlayer Water Molecules

Real-time control over infrared (IR) radiation of objects is highly desired in a variety of areas such as personal thermal regulation and IR camouflage. This requires the dynamic modulation of IR emissivity in a stepless manner over a wide range (>50%), which remains a daunting challenge. Here, an emissivity modulation phenomenon is reported in stacked 2D Ti3 C2 Tx MXene nanosheets, from 12% to 68% as the intercalation/discharging of water molecules within the interlayers. The intercalation of water molecules dynamically changes the electronic properties and the complex permittivity in IR frequencies of Ti3 C2 Tx . This emissivity modulation is a stepless and reversible process without the assistance of any external energy input. Further, intercalating cellulose nanofibers into the Ti3 C2 Tx interlayers makes this dynamic process highly repeatable. Last, a sweat-responsive adaptive textile that can improve thermal comfort of human body under changes in metabolic rates and environmental conditions is demonstrated, showing great potential of this mechanism in passive on-demand radiation modulation.

Bent π-Conjugation within a Macrocycle: Asymmetric Total Syntheses of Spirohexenolides A and B

Macrocycles with bent π-conjugation motif are extremely rare in nature and synthetically daunting and anticancer haouamines and spirohexenolides were representative of such rare natural products with synthetically challenging bent π-conjugation within a macrocycle. While the total synthesis of haouamines has been elegantly achieved, spirohexenolides remains an unmet synthetic challenge due to the highly strained bent 1,3,5-triene conjugation within C15 macrocycle. Inspired by the chemical synthesis of cycloparaphenylenes (CPPs) and haouamines, herein we devise a synthetic strategy to overcome the highly strained bent 1,3,5-triene conjugation within the macrocycle and achieve the first, asymmetric total synthesis of spirohexenolides A (>20 mg) and B (>50 mg). Our synthesis features strategic design of ring-closing metathesis (RCM) macrocyclization followed by double dehydration to achieve the C15 macrocycle with the deformed nonplanar 1,3,5-triene conjugation. In addition, we have developed a new enantioselective construction of highly functionalized spirotetronate fragment (northeast moiety) through RCM and Ireland-Claisen rearrangement. Our in vitro bioassay studies reveal that both spirohexenolides are cytotoxic against a panel of human cancer cells with IC50 1.2-13.3 μM and spirohexenolide A is consistently more potent (up to 3 times) than spirohexenolide B, suggesting the importance of alcohol for their bioactivity and for medicinal chemistry development.

Short, Scalable Access to Pyrrovobasine

A concise gram-scale synthesis of pyrrovobasine (1) is reported. Key transformations include a three-step decagram-scale synthesis of the tetracyclic compound, Mn-mediated direct radical cyclization, and the introduction of a naturally rare pyrraline structure. The synthesis is designed to be applicable to gram-scale synthesis using inexpensive and readily available reagents.

Standardized local assortativity in networks and systemic risk in financial markets

The study of assortativity allows us to understand the heterogeneity of networks and the implication of network resilience. While a global measure has been predominantly used to characterize this network feature, there has been little research to suggest a local coefficient to account for the presence of local (dis)assortative patterns in diversely mixed networks. We build on existing literature and extend the concept of assortativity with the proposal of a standardized scale-independent local coefficient to observe the assortative characteristics of each entity in networks that would otherwise be smoothed out with a global measure. This coefficient provides a lens through which the granular level of details can be observed, as well as capturing possible pattern (dis)formation in dynamic networks. We demonstrate how the standardized local assortative coefficient discovers the presence of (dis)assortative hubs in static networks on a granular level, and how it tracks systemic risk in dynamic financial networks.

A Highly Transparent Photo-Electro-Thermal Film with Broadband Selectivity for All-Day Anti-/De-Icing

A photo- and electro-thermal film can convert sunlight and electricity into heat to solve icing problems. Combination of them provides an efficient strategy for all-day anti-/de-icing. However, only opaque surfaces have been reported, due to the mutual exclusiveness between photon absorption and transmission. Herein, a highly transparent and scalable solution-processed photo-electro-thermal film is reported, which exhibits an ultra-broadband selective spectrum to separate the visible light from sunlight and a countertrend suppress of emission in longer wavelength. It absorbs ≈ 85% of invisible sunlight (ultraviolet and near-infrared) for light-heat conversion, meanwhile maintains luminous transmittance > 70%. The reflection of mid-infrared leads to low emissivity (0.41), which further preserves heat on the surface for anti-/de-icing purpose. This ultra-broadband selectivity enables temperature elevation > 40 °C under 1-sun illumination and the mutual support between photo-thermal and electro-thermal effects contributes to > 50% saving of electrical consumption under weak solar exposure (0.4-sun) for maintaining unfrozen surfaces at -35 °C environment. The reverberation from photo-electro-thermal and super-hydrophobic effects illustrates a lubricating removal of grown ice in short time (< 120 s). The self-cleaning ability and the durability under mechanical, electrical, optical, and thermal stresses render the film stable for long-term usage in all-day anti-/de-icing applications.

ECL 3.0: a sensitive peptide identification tool for cross-linking mass spectrometry data analysis

BACKGROUND

Cross-linking mass spectrometry (XL-MS) is a powerful technique for detecting protein-protein interactions (PPIs) and modeling protein structures in a high-throughput manner. In XL-MS experiments, proteins are cross-linked by a chemical reagent (namely cross-linker), fragmented, and then fed into a tandem mass spectrum (MS/MS). Cross-linkers are either cleavable or non-cleavable, and each type requires distinct data analysis tools. However, both types of cross-linkers suffer from imbalanced fragmentation efficiency, resulting in a large number of unidentifiable spectra that hinder the discovery of PPIs and protein conformations. To address this challenge, researchers have sought to improve the sensitivity of XL-MS through invention of novel cross-linking reagents, optimization of sample preparation protocols, and development of data analysis algorithms. One promising approach to developing new data analysis methods is to apply a protein feedback mechanism in the analysis. It has significantly improved the sensitivity of analysis methods in the cleavable cross-linking data. The application of the protein feedback mechanism to the analysis of non-cleavable cross-linking data is expected to have an even greater impact because the majority of XL-MS experiments currently employs non-cleavable cross-linkers.

RESULTS

In this study, we applied the protein feedback mechanism to the analysis of both non-cleavable and cleavable cross-linking data and observed a substantial improvement in cross-link spectrum matches (CSMs) compared to conventional methods. Furthermore, we developed a new software program, ECL 3.0, that integrates two algorithms and includes a user-friendly graphical interface to facilitate wider applications of this new program.

CONCLUSIONS

ECL 3.0 source code is available at https://github.com/yuweichuan/ECL-PF.git . A quick tutorial is available at https://youtu.be/PpZgbi8V2xI .

Temperature sensitivity of the interspecific interaction strength of coastal marine fish communities

The effects of temperature on interaction strengths are important for understanding and forecasting how global climate change impacts marine ecosystems; however, tracking and quantifying interactions of marine fish species are practically difficult especially under field conditions, and thus, how temperature influences their interaction strengths under field conditions remains poorly understood. We herein performed quantitative fish environmental DNA (eDNA) metabarcoding on 550 seawater samples that were collected twice a month from 11 coastal sites for 2 years in the Boso Peninsula, Japan, and analyzed eDNA monitoring data using nonlinear time series analytical tools. We detected fish-fish interactions as information flow between eDNA time series, reconstructed interaction networks for the top 50 frequently detected species, and quantified pairwise, fluctuating interaction strengths. Although there was a large variation, water temperature influenced fish-fish interaction strengths. The impact of water temperature on interspecific interaction strengths varied among fish species, suggesting that fish species identity influences the temperature effects on interactions. For example, interaction strengths that Halichoeres tenuispinis and Microcanthus strigatus received strongly increased with water temperature, while those of Engraulis japonicus and Girella punctata decreased with water temperature. An increase in water temperature induced by global climate change may change fish interactions in a complex way, which consequently influences marine community dynamics and stability. Our research demonstrates a practical research framework to study the effects of environmental variables on interaction strengths of marine communities in nature, which would contribute to understanding and predicting natural marine ecosystem dynamics.

Gel transformation as a general strategy for fabrication of highly porous multiscale MOF architectures

The structure and chemistry of metal-organic frameworks or MOFs dictate their properties and functionalities. However, their architecture and form are essential for facilitating the transport of molecules, the flow of electrons, the conduction of heat, the transmission of light, and the propagation of force, which are vital in many applications. This work explores the transformation of inorganic gels into MOFs as a general strategy to construct complex porous MOF architectures at nano, micro, and millimeter length scales. MOFs can be induced to form along three different pathways governed by gel dissolution, MOF nucleation, and crystallization kinetics. Slow gel dissolution, rapid nucleation, and moderate crystal growth result in a pseudomorphic transformation (pathway 1) that preserves the original network structure and pores, while a comparably faster crystallization displays significant localized structural changes but still preserves network interconnectivity (pathway 2). MOF exfoliates from the gel surface during rapid dissolution, thus inducing nucleation in the pore liquid leading to a dense assembly of percolated MOF particles (pathway 3). Thus, the prepared MOF 3D objects and architectures can be fabricated with superb mechanical strength (>98.7 MPa), excellent permeability (>3.4 × 10^-10 m²), and large surface area (1100 m² g^-1) and mesopore volumes (1.1 cm³ g^-1).

Selective multifunctionalization of N-heterocyclic carbene boranes via the intermediacy of boron-centered radicals

The selective difunctionalization of N-heterocyclic carbene (NHC) boranes with alkenes has been achieved via decatungstate and thiol synergistic catalysis. The catalytic system also allows stepwise trifunctionalization, leading to complex NHC boranes with three different functional groups which are challenging to prepare by other methods. The strong hydrogen-abstracting ability of the excited decatungstate enables the generation of boryl radicals from mono- and di-substituted boranes for realizing borane multifunctionalization. This proof-of-principle research provides a new chance for fabricating unsymmetrical boranes and developing boron-atom-economic synthesis.

A UV-Reflective Organic-Inorganic Tandem Structure for Efficient and Durable Daytime Radiative Cooling in Harsh Climates

Radiative cooling shows great promise in eco-friendly space cooling due to its zero-energy consumption. For subambient cooling in hot humid subtropical/tropical climates, achieving ultrahigh solar reflectance (≥96%), durable ultraviolet (UV) resistance, and surface superhydrophobicity simultaneously is critical, which, however, is challenging for most state-of-the-art scalable polymer-based coolers. Here an organic-inorganic tandem structure is reported to address this challenge, which comprises a bottom high-refractive-index polyethersulfone (PES) cooling layer with bimodal honeycomb pores, an alumina (Al₂ O₃ ) nanoparticle UV reflecting layer with superhydrophobicity, and a middle UV absorption layer of titanium dioxide (TiO₂ ) nanoparticles, thus providing thorough protection from UV and self-cleaning capability together with outstanding cooling performance. The PES-TiO₂ -Al₂ O₃ cooler demonstrates a record-high solar reflectance of over 0.97 and high mid-infrared emissivity of 0.92, which can maintain their optical properties intact even after equivalent 280-day UV exposure despite the UV-sensitivity of PES. This cooler achieves a subambient cooling temperature up to 3 °C at summer noontime and 5 °C at autumn noontime without solar shading or convection cover in a subtropical coastal city, Hong Kong. This tandem structure can be extended to other polymer-based designs, offering a UV-resist but reliable radiative cooling solution in hot humid climates.

Carrier Dynamics of Efficient Triplet Harvesting in AgBiS2 /Pentacene Singlet Fission Solar Cells

Singlet fission is a process by which an organic semiconductor is able to generate two triplet excitons from a single photon. If charges from the triplets can be successfully harvested without heavy losses in energy, then this process can enable a single-junction solar cell to surpass the Shockley-Queisser limit. While singlet fission processes are commonly observed in several materials, harvesting the resulting triplets is difficult and has been demonstrated with only a few transport materials. Here, transient absorption spectroscopy is used to investigate singlet fission and carrier transfer processes at the AgBiS₂ /pentacene (AgBiS₂ /Pc) heterojunction. The successful transfer of triplets from pentacene to AgBiS₂ and the transfer of holes from AgBiS₂ to pentacene is observed. Further singlet fission in pentacene by modifying the crystallinity of the pentacene layer and have fabricated the first singlet fission AgBiS₂ /Pc solar cell is enhanced. Singlet fission devices exhibit higher external quantum efficiency compared with the control devices, and thus demonstrating the significant contribution of charges from the singlet fission process.

Dissolvable Topical Formulations for Burst and Constant Delivery of Vitamin C

Healthy skin has a high vitamin C concentration that protects against ultraviolet (UV)-induced damage, promotes wound healing, and lowers cancer risk. The present contribution describes two drug delivery systems for topical administration of vitamin C. The electrospun poly(vinyl alcohol) (PVA) nanofiber carrier of vitamin C exhibits a burst release profile (66 mg/g/h followed by 6.3 mg/g/h). In comparison, a new composite PVA nanofiber-molecular capsule delivers vitamin C at a constant rate (8.2 mg/g/h) with a zeroth-order release profile for better therapeutic management. Both delivery systems protect vitamin C and afford increased heat stability. The molecular capsules of β-cyclodextrin with the vitamin C inclusion complex are immobilized on cellulose acetate and electrosprayed onto an electrospun PVA nanofiber mat.

Computational capability of ecological dynamics

Ecological dynamics is driven by complex ecological networks. Computational capabilities of artificial networks have been exploited for machine learning purposes, yet whether an ecological network possesses a computational capability and whether/how we can use it remain unclear. Here, we developed two new computational/empirical frameworks based on reservoir computing and show that ecological dynamics can be used as a computational resource. In silico ecological reservoir computing (ERC) reconstructs ecological dynamics from empirical time series and uses simulated system responses for information processing, which can predict near future of chaotic dynamics and emulate nonlinear dynamics. The real-time ERC uses real population dynamics of a unicellular organism, Tetrahymena thermophila. The temperature of the medium is an input signal and population dynamics is used as a computational resource. Intriguingly, the real-time ecological reservoir has necessary conditions for computing (e.g. synchronized dynamics in response to the same input sequences) and can make near-future predictions of empirical time series, showing the first empirical evidence that population-level phenomenon is capable of real-time computations. Our finding that ecological dynamics possess computational capability poses new research questions for computational science and ecology: how can we efficiently use it and how is it actually used, evolved and maintained in an ecosystem?

The spectrum of covariance matrices of randomly connected recurrent neuronal networks with linear dynamics

A key question in theoretical neuroscience is the relation between the connectivity structure and the collective dynamics of a network of neurons. Here we study the connectivity-dynamics relation as reflected in the distribution of eigenvalues of the covariance matrix of the dynamic fluctuations of the neuronal activities, which is closely related to the network dynamics’ Principal Component Analysis (PCA) and the associated effective dimensionality. We consider the spontaneous fluctuations around a steady state in a randomly connected recurrent network of stochastic neurons. An exact analytical expression for the covariance eigenvalue distribution in the large-network limit can be obtained using results from random matrices. The distribution has a finitely supported smooth bulk spectrum and exhibits an approximate power-law tail for coupling matrices near the critical edge. We generalize the results to include second-order connectivity motifs and discuss extensions to excitatory-inhibitory networks. The theoretical results are compared with those from finite-size networks and the effects of temporal and spatial sampling are studied. Preliminary application to whole-brain imaging data is presented. Using simple connectivity models, our work provides theoretical predictions for the covariance spectrum, a fundamental property of recurrent neuronal dynamics, that can be compared with experimental data.

Here we study the distribution of eigenvalues, or spectrum, of the neuron-to-neuron covariance matrix in recurrently connected neuronal networks. The covariance spectrum is an important global feature of neuron population dynamics that requires simultaneous recordings of neurons. The spectrum is essential to the widely used Principal Component Analysis (PCA) and generalizes the dimensionality measure of population dynamics. We use a simple model to emulate the complex connections between neurons, where all pairs of neurons interact linearly at a strength specified randomly and independently. We derive a closed-form expression of the covariance spectrum, revealing an interesting long tail of large eigenvalues following a power law as the connection strength increases. To incorporate connectivity features important to biological neural circuits, we generalize the result to networks with an additional low-rank connectivity component that could come from learning and networks consisting of sparsely connected excitatory and inhibitory neurons. To facilitate comparing the theoretical results to experimental data, we derive the precise modifications needed to account for the effect of limited time samples and having unobserved neurons. Preliminary applications to large-scale calcium imaging data suggest our model can well capture the high dimensional population activity of neurons.

Beyond Conformational Control: Effects of Noncovalent Interactions on Molecular Electronic Properties of Conjugated Polymers

Tuning the electronic properties of polymers is of great importance in designing highly efficient organic solar cells. Noncovalent intramolecular interactions have been often used for conformational control to enhance the planarity of polymers or molecules, which may reduce band gaps and promote charge transfer. However, it is not known if noncovalent interactions may alter the electronic properties of conjugated polymers through some mechanism other than the conformational control. Here, we studied the effects of various noncovalent interactions, including sulfur-nitrogen, sulfur-oxygen, sulfur-fluorine, oxygen-nitrogen, oxygen-fluorine, and nitrogen-fluorine, on the electronic properties of polymers with planar geometry using unconstrained and constrained density functional theory. We found that the sulfur-nitrogen intramolecular interaction may reduce the band gaps of polymers and enhance the charge transfer more obviously than other noncovalent interactions. Our findings are also consistent with the experimental data. For the first time, our study shows that the sulfur-nitrogen noncovalent interaction may further affect the electronic structure of coplanar conjugated polymers, which cannot be only explained by the enhancement of molecular planarity. Our work suggests a new mechanism to manipulate the electronic properties of polymers to design high-performance small-molecule-polymer and all-polymer solar cells.

Low-Density Lipoprotein Receptor-Related Protein 6 Cell Surface Availability Regulates Fuel Metabolism in Astrocytes

Early changes in astrocyte energy metabolism are associated with late-onset Alzheimer's disease (LOAD), but the underlying mechanism remains elusive. A previous study suggested an association between a synonymous SNP (rs1012672, C→T) in LRP6 gene and LOAD; and that is indeed correlated with diminished LRP6 gene expression in the frontal cortex region. The authors show that LRP6 is a unique Wnt coreceptor on astrocytes, serving as a bimodal switch that modulates their metabolic landscapes. The Wnt-LRP6 mediated mTOR-AKT axis is essential for sustaining glucose metabolism. In its absence, Wnt switches to activate the LRP6-independent Ca2+ -PKC-NFAT axis, resulting in a transcription network that favors glutamine and branched chain amino acids (BCAAs) catabolism over glucose metabolism. Exhaustion of these raw materials essential for neurotransmitter biosynthesis and recycling results in compromised synaptic, cognitive, and memory functions; priming for early changes that are frequently found in LOAD. The authors also highlight that intranasal supplementation of glutamine and BCAAs is effective in preserving neuronal integrity and brain functions, proposing a nutrient-based method for delaying cognitive and memory decline when LRP6 cell surface levels and functions are suboptimal.

Symmetry-breaking-induced rare fluctuations in a time-delay dynamic system

Inspired by the experimental and numerical findings, we study the dynamic instabilities of two coupled nonlinear delay differential equations that are used to describe the coherent oscillations between the top and bottom boundary layers in turbulent Rayleigh-Bénard convection. By introducing two sensitivity parameters for the instabilities of the top and bottom boundary layers, we find three different types of solutions, namely in-phase single-period oscillations, multi-period oscillations and chaos. The chaos solution contains rare but large amplitude fluctuations. The statistical properties of these fluctuations are consistent with those observed in the experiment for the massive eruption of thermal plumes, which causes random reversals of the large-scale circulation in turbulent Rayleigh-Bénard convection. Our study thus provides new insights into the origin of rare massive eruptions and sudden changes of large-scale flow pattern that are often observed in convection systems of geophysical and astrophysical scales.

Adaptive optics two-photon endomicroscopy enables deep-brain imaging at synaptic resolution over large volumes

Optical deep-brain imaging in vivo at high resolution has remained a great challenge over the decades. Two-photon endomicroscopy provides a minimally invasive approach to image buried brain structures, once it is integrated with a gradient refractive index (GRIN) lens embedded in the brain. However, its imaging resolution and field of view are compromised by the intrinsic aberrations of the GRIN lens. Here, we develop a two-photon endomicroscopy by adding adaptive optics based on direct wavefront sensing, which enables recovery of diffraction-limited resolution in deep-brain imaging. A new precompensation strategy plays a critical role to correct aberrations over large volumes and achieve rapid random-access multiplane imaging. We investigate the neuronal plasticity in the hippocampus, a critical deep brain structure, and reveal the relationship between the somatic and dendritic activity of pyramidal neurons.

Sub-wavelength focusing of acoustic waves in bubbly media

The purpose of this paper is to investigate acoustic wave scattering by a large number of bubbles in a liquid at frequencies near the Minnaert resonance frequency. This bubbly media has been exploited in practice to obtain super-focusing of acoustic waves. Using layer potential techniques, we derive the scattering function for a single spherical bubble excited by an incident wave in the low frequency regime. We then propose a point scatterer approximation for N bubbles, and describe several numerical simulations based on this approximation, that demonstrate the possibility of achieving super-focusing using bubbly media.