Engineering ion-framed porous organic polymer for synergistic high-capacity adsorption and ultra-trace recovery of gold.

Developing advanced functional adsorbents capable of selectively recovering gold from electronic waste (e-waste) and enriching trace amounts of gold from seawater is a critical technical imperative for advancing a sustainable economy. In this study, a cationic pyridine porphyrin-based porous organic polymer (Pyd-PPOPs-Br) was rationally designed and presented via a one-pot bottom-up approach by integrating cationic pyridine-based building blocks with pyrrole. The incorporation of positively charged pyridine sites and redox-active porphyrin rings conferred Pyd-PPOPs-Br with an ultrahigh gold recovery capacity of 3.

Applying Space-Group Symmetry to Speed Up Hybrid-Functional Calculations within the Framework of Numerical Atomic Orbitals.

Building upon the efficient implementation of hybrid density functionals (HDFs) for large-scale periodic systems within the framework of numerical atomic orbital bases using the localized resolution of identity (RI) technique, we have developed an algorithm that exploits the space group symmetry in key operation steps of HDF calculations, leading to further improvements in two ways. First, the reduction of -points in the Brillouin zone can reduce the number of Kohn-Sham equations to be solved. This necessitates the correct implementation of the rotation relation between the density matrices of equivalent -points within the representation of atomic orbitals.

A Deep Learning Framework for the Electronic Structure of Water: Toward a Universal Model.

Accurately modeling the electronic structure of water across scales, from individual molecules to bulk liquid, remains a grand challenge. Traditional computational methods face a critical trade-off between computational cost and efficiency. We present an enhanced machine-learning Deep Kohn-Sham (DeePKS) method for improved electronic structure, DeePKS-ES, that overcomes this dilemma.

Intrinsic strain of defect sites steering chlorination reaction for water purification.

Carbon nanotube (CNT)-based heterogeneous advanced oxidation processes (AOPs) used for water purification have been exploited for several decades. Many strategies for modifying CNTs have been utilized to improve their catalytic performance in remediation processes. However, the strain fields of the intrinsic defect sites on CNT steering AOPs (such as chlorination) have not yet been reported.

LOX-induced tubulointerstitial fibrosis via the TGF-β/LOX/Snail axis in diabetic mice.

Background: The partial epithelial-mesenchymal transition (EMT) is emerging as a significant mechanism in diabetic nephropathy (DN). LOX is a copper amine oxidase conventionally thought to act by crosslinking collagen. However, the role of LOX in partial EMT and fibrotic progression in diabetic nephropathy has not been investigated experimentally.

Enhanced water stability of MOFs multiple hydrogen bonds and their application in water harvesting.

A mechanism based on multiple hydrogen bonds was proposed to describe the great water stability of some hydrated Cu paddle-wheel-based MOFs, which was demonstrated through density functional theory (DFT) calculations and single-crystal X-ray diffraction (SCXRD) of water-loaded MOFs. This mechanism endowed Cu-TDPAT with exceptional water stability and outstanding atmospheric water harvesting capability.

Machine-Learning-Based Interatomic Potentials for Group IIB to VIA Semiconductors: Toward a Universal Model.

Rapid advancements in machine-learning methods have led to the emergence of machine-learning-based interatomic potentials as a new cutting-edge tool for simulating large systems with ab initio accuracy. Still, the community awaits universal interatomic models that can be applied to a wide range of materials without tuning neural network parameters. We develop a unified deep-learning interatomic potential (the DPA-Semi model) for 19 semiconductors ranging from group IIB to VIA, including Si, Ge, SiC, BAs, BN, AlN, AlP, AlAs, InP, InAs, InSb, GaN, GaP, GaAs, CdTe, InTe, CdSe, ZnS, and CdS.

Fork coupling directs DNA replication elongation and termination.

DNA replication is initiated at multiple loci to ensure timely duplication of eukaryotic genomes. Sister replication forks progress bidirectionally, and replication terminates when two convergent forks encounter one another. To investigate the coordination of replication forks, we developed a replication-associated in situ HiC method to capture chromatin interactions involving nascent DNA.

DPA-2: a large atomic model as a multi-task learner.

The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demonstrated the capability to conduct large-scale, long-duration simulations with the accuracy of electronic structure methods. However, the model generation process remains a bottleneck for large-scale applications.

Cooperatively designed aptamer-PROTACs for spatioselective degradation of nucleocytoplasmic shuttling protein for enhanced combinational therapy.

Nucleocytoplasmic shuttling proteins (NSPs) have emerged as a promising class of therapeutic targets for many diseases. However, most NSPs-based therapies largely rely on small-molecule inhibitors with limited efficacy and off-target effects. Inspired by proteolysis targeting chimera (PROTAC) technology, we report a new archetype of PROTAC (PS-ApTCs) by introducing a phosphorothioate-modified aptamer to a CRBN ligand, realizing tumor-targeting and spatioselective degradation of NSPs with improved efficacy.

Speciation of La-Cl Complexes in Hydrothermal Fluids from Deep Potential Molecular Dynamics.

The stability of rare earth element (REE) complexes plays a crucial role in quantitatively assessing their hydrothermal migration and transformation. However, reliable data are lacking under high-temperature hydrothermal conditions, which hampers our understanding of the association behavior of REE. Here a deep learning potential model for the LaCl-HO system in hydrothermal fluids is developed based on the first-principles density functional theory calculations.

A cocktail therapeutic strategy based on clofarabine-containing aptamer-PROTAC for enhanced cancer therapy.

By introducing a therapeutic nucleoside analogue tail to the parent Aptamer-PROTACs, a PROTAC-cocktail system (ApTCs-3X) was designed and evaluated. ApTCs-3X exhibited improved nuclease resistance and efficiently degraded target protein with subcellular localization preference. This cocktail therapy results in enhanced therapeutic outcomes, making it suitable for advancing PROTAC in combination therapy.

Implementation of the meta-GGA exchange-correlation functional in numerical atomic orbital basis: With systematic testing on SCAN, rSCAN, and r2SCAN functionals.

Kohn-Sham density functional theory (DFT) is nowadays widely used for electronic structure theory simulations, and the accuracy and efficiency of DFT rely on approximations of the exchange-correlation functional. By including the kinetic energy density τ, the meta-generalized-gradient approximation (meta-GGA) family of functionals achieves better accuracy and flexibility while retaining the efficiency of semi-local functionals. For example, the strongly constrained and appropriately normed (SCAN) meta-GGA functional has been proven to yield accurate results for solid and molecular systems.

Characterization of the Hydrogen-Bond Network in High-Pressure Water by Deep Potential Molecular Dynamics.

The hydrogen-bond (H-bond) network of high-pressure water is investigated by neural-network-based molecular dynamics (MD) simulations with first-principles accuracy. The static structure factors (SSFs) of water at three densities, i.e.

Cohesin maintains replication timing to suppress DNA damage on cancer genes.

Cohesin loss-of-function mutations are frequently observed in tumors, but the mechanism underlying its role in tumorigenesis is unclear. Here, we found that depletion of RAD21, a core subunit of cohesin, leads to massive genome-wide DNA breaks and 147 translocation hotspot genes, co-mutated with cohesin in multiple cancers. Increased DNA damages are independent of RAD21-loss-induced transcription alteration and loop anchor disruption.

Rational Design of Trident Aptamer Scaffold for Rapid and Accurate Monitoring of 25-Hydroxyvitamin D Metabolism in Living Cells.

The level of 25-hydroxyvitamin D [25(OH)VD3] in human blood is considered as the best indicator of vitamin D status, and its deficiency or excess can lead to various health problems. Current methods for monitoring 25(OH)VD3 metabolism in living cells have limitations in terms of sensitivity and specificity and are often expensive and time-consuming. To address these issues, an innovative trident scaffold-assisted aptasensor (TSA) system has been developed for the online quantitative monitoring of 25(OH)VD3 in complex biological environments.

ZIF-67 Incorporated Sulfonated Poly (Aryl Ether Sulfone) Mixed Matrix Membranes for Pervaporation Separation of Methanol/Methyl Tert-Butyl Ether Mixture.

Mixed matrix membranes (MMMs) with nano-fillers dispersed in polymer matrix have been proposed as alternative pervaporation membrane materials. They possess both promising selectivity benefiting from the fillers and economical processing capabilities of polymers. ZIF-67 was synthesized and incorporated into the sulfonated poly (aryl ether sulfone) (SPES) matrix to prepare SPES/ZIF-67 mixed matrix membranes with different ZIF-67 mass fractions.

Carbon Nanodots Memristor: An Emerging Candidate toward Artificial Biosynapse and Human Sensory Perception System.

In the era of big data and artificial intelligence (AI), advanced data storage and processing technologies are in urgent demand. The innovative neuromorphic algorithm and hardware based on memristor devices hold a promise to break the von Neumann bottleneck. In recent years, carbon nanodots (CDs) have emerged as a new class of nano-carbon materials, which have attracted widespread attention in the applications of chemical sensors, bioimaging, and memristors.

An orthogonally activatable CRISPR-Cas13d nanoprodrug to reverse chemoresistance for enhanced chemo-photodynamic therapy.

Orthogonal therapy that combines CRISPR-based gene editing and prodrug-based chemotherapy is a promising approach to combat multidrug-resistant cancer. However, its potency to precisely regulate different therapeutic modalities is limited due to the lack of an integrated platform with high spatiotemporal resolution. Taking advantage of CRISPR technology, a Pt(iv)-based prodrug and orthogonal emissive upconversion nanoparticles (UCNPs), we herein rationally designed the first logic-gated CRISPR-Cas13d-based nanoprodrug for orthogonal photomodulation of gene editing and prodrug release for enhanced cancer therapy.

Theoretical study on the free radical scavenging potency and mechanism of natural coumestans: Roles of substituent, noncovalent interaction and solvent.

The free radical scavenging potency and mechanisms of seven representative natural coumestans were systematically evaluated using density functional theory (DFT) approach. Thermodynamic feasibility of different mechanisms was assessed by various physio-chemical descriptors involved in the double (2H/2e) radical-trapping processes. Energy diagram and related transition state structures of the reaction between wedelolactone (WEL) and hydroperoxyl radical were constructed to further uncover the radical-trapping details.

Low-Cost Antimony Selenosulfide with Tunable Bandgap for Highly Efficient Solar Cells.

About 10% efficient antimony selenosulfide (Sb (S,Se) ) solar cell is realized by using selenourea as a hydrothermal raw material to prepare absorber layers. However, tailoring the bandgap of hydrothermal-based Sb (S,Se) film to the ideal bandgap (1.3-1.

Solvation structures of calcium and magnesium ions in water with the presence of hydroxide: a study by deep potential molecular dynamics.

The solvation structures of calcium (Ca) and magnesium (Mg) ions with the presence of hydroxide (OH) ion in water are essential for understanding their roles in biological and chemical processes but have not been fully explored. molecular dynamics (AIMD) is an important tool to address this issue, but two challenges exist. First, an accurate description of OH from AIMD needs an appropriate exchange-correlation functional.

Neural Network-Based Autonomous Search Model with Undulatory Locomotion Inspired by .

() exhibits sophisticated chemotaxis behavior with a unique locomotion pattern using a simple nervous system only and is, therefore, well suited to inspire simple, cost-effective robotic navigation schemes. Chemotaxis in involves two complementary strategies: klinokinesis, which allows reorientation by sharp turns when moving away from targets; and klinotaxis, which gradually adjusts the direction of motion toward the preferred side throughout the movement. In this study, we developed an autonomous search model with undulatory locomotion that combines these two chemotaxis strategies with its body undulatory locomotion.

Dynamic Graph Message Passing Networks.

Modelling long-range dependencies is critical for scene understanding tasks in computer vision. Although convolution neural networks (CNNs) have excelled in many vision tasks, they are still limited in capturing long-range structured relationships as they typically consist of layers of local kernels. A fully-connected graph, such as the self-attention operation in Transformers, is beneficial for such modelling, however, its computational overhead is prohibitive.