Theoretical insights on potential-dependent oxidation behaviors and antioxidant strategies of MXenes.

Significant efforts have been devoted to investigating the oxidation of MXenes in various environments. However, the underlying mechanism of MXene oxidation and its dependence on the electrode potential remain poorly understood. Here we show the oxidation behavior of MXenes under the working conditions of electrochemical processes in terms of kinetics and thermodynamics by using constant-potential ab initio simulations.

Transferable performance of machine learning potentials across graphene-water systems of different sizes: Insights from numerical metrics and physical characteristics.

Machine learning potentials (MLPs) are promising for various chemical systems, but their complexity and lack of physical interpretability challenge their broad applicability. This study evaluates the transferability of the deep potential (DP) and neural equivariant interatomic potential (NequIP) models for graphene-water systems using numerical metrics and physical characteristics. We found that the data quality from density functional theory calculations significantly influences MLP predictive accuracy.

Identification of Cold Tolerance Transcriptional Regulatory Genes in Seedlings of L. and L.

Alfalfa species L. (MS) and L. (MF), globally prominent perennial leguminous forages, hold substantial economic value.

Proton-Driven Dynamic Behavior of Nanoconfined Water in Hydrophilic MXene Sheets.

Liquid water under nanoscale confinement has attracted intensive attention due to its pivotal role in understanding various phenomena across many scientific fields. MXenes serve an ideal paradigm for investigating the dynamic behaviors of nanoconfined water in a hydrophilic environment. Combining deep neural networks and an active learning scheme, here we elucidate the proton-driven dynamics of water molecules confined between VCT sheets using molecular dynamics simulation.

Rupatadine-inhibited OTUD3 promotes DLBCL progression and immune evasion through deubiquitinating MYL12A and PD-L1.

The obstacle to effectively treating Diffuse Large B-cell Lymphoma (DLBCL) lies in the resistance observed toward standard therapies. Identifying therapeutic targets that prove effective for relapsed or refractory patients poses a significant challenge. OTUD3, a deubiquitinase enzyme, is overexpressed in DLBCL tissues.

Early warning and proactive control strategies for power blackouts caused by gas network malfunctions.

There is growing consensus that gas-fired generators will play a crucial role during the transition to net-zero energy systems, both as an alternative to coal-fired generators and as a flexibility service provider for power systems. However, malfunctions of gas networks have caused several large-scale power blackouts. The transition from coal and oil to gas fuels significantly increases the interdependence between gas networks and electric power systems, raising the risks of more frequent and widespread power blackouts due to the malfunction of gas networks.

Multi-resource dynamic coordinated planning of flexible distribution network.

The flexible distribution network presents a promising architecture to accommodate highly integrated distributed generators and increasing loads in an efficient and cost-effective way. The distribution network is characterised by flexible interconnections and expansions based on soft open points, which enables it to dispatch power flow over the entire system with enhanced controllability and compatibility. Herein, we propose a multi-resource dynamic coordinated planning method of flexible distribution network that allows allocation strategies to be determined over a long-term planning period.

Rolapitant treats lung cancer by targeting deubiquitinase OTUD3.

Background: Lung cancer is cancer with the highest morbidity and mortality in the world and poses a serious threat to human health. Therefore, discovering new treatments is urgently needed to improve lung cancer prognosis. Small molecule inhibitors targeting the ubiquitin-proteasome system have achieved great success, in which deubiquitinase inhibitors have broad clinical applications.

A comprehensive transformer-based approach for high-accuracy gas adsorption predictions in metal-organic frameworks.

Gas separation is crucial for industrial production and environmental protection, with metal-organic frameworks (MOFs) offering a promising solution due to their tunable structural properties and chemical compositions. Traditional simulation approaches, such as molecular dynamics, are complex and computationally demanding. Although feature engineering-based machine learning methods perform better, they are susceptible to overfitting because of limited labeled data.

Genome Sequencing and Analysis of , a Rice Leaf Disease Fungus.

is one of several fungal pathogens known to cause brown streaks, leaf spots, and latent infections in rice. In this study, the entire 42.09-Mb genome of was sequenced at a depth of 169× using the Oxford Nanopore Technologies platform.

Unveiling the Role of Electrostatic Forces on Attraction between Opposing Polyelectrolyte Brushes.

Electrostatic interaction and molecular excluded-volume effects are responsible for a plethora of nonintuitive phenomena in soft-matter systems, including local charge inversion and attraction between similar charges. In the current work, we study the surface forces and swelling behavior of opposing polyelectrolyte brushes using a classical density functional theory that accounts for electrostatic and excluded-volume correlations. We observe that the detachment pressure between similarly charged brushes is sensitive to salt concentration in both the osmotic and salted regimes and can be negative in the presence of multivalent counterions.

Single-chain simulation of Ising density functional theory for weak polyelectrolytes.

Conventional theories of weak polyelectrolytes are either computationally prohibitive to account for the multidimensional inhomogeneity of polymer ionization in a liquid environment or oversimplistic in describing the coupling effects of ion-explicit electrostatic interactions and long-range intrachain correlations. To bridge this gap, we implement the Ising density functional theory (iDFT) for ionizable polymer systems using the single-chain-in-mean-field algorithm. The single-chain-in-iDFT (sc-iDFT) shows significant improvements over conventional mean-field methods in describing segment-level dissociation equilibrium, specific ion effects, and long-range intrachain correlations.

Perfecting Liquid-State Theories with Machine Intelligence.

Recent years have seen a significant increase in the use of machine intelligence for predicting the electronic structure, molecular force fields, and physicochemical properties of various condensed systems. However, substantial challenges remain in developing a comprehensive framework capable of handling a wide range of atomic compositions and thermodynamic conditions. This perspective discusses potential future developments in liquid-state theories leveraging recent advancements in functional machine learning.

Designing artificial ion channels with strict K/Na selectivity toward next-generation electric-eel-mimetic ionic power generation.

A biological potassium channel is >1000 times more permeable to K than to Na and exhibits a giant permeation rate of ∼10 ions/s. It is a great challenge to construct artificial potassium channels with such high selectivity and ion conduction rate. Herein, we unveil a long-overlooked structural feature that underpins the ultra-high K/Na selectivity.

Superstructural ordering in self-sorting coacervate-based protocell networks.

Bottom-up assembly of higher-order cytomimetic systems capable of coordinated physical behaviours, collective chemical signalling and spatially integrated processing is a key challenge in the study of artificial multicellularity. Here we develop an interactive binary population of coacervate microdroplets that spontaneously self-sort into chain-like protocell networks with an alternating sequence of structurally and compositionally dissimilar microdomains with hemispherical contact points. The protocell superstructures exhibit macromolecular self-sorting, spatially localized enzyme/ribozyme biocatalysis and interdroplet molecular translocation.

Serum VEGF levels as a predictor of recurrence in patients with advanced‑stage esophageal squamous cell carcinoma following curative esophagectomy followed by chemotherapy or concurrent radiotherapy.

The present study evaluated serum levels of vascular endothelial growth factor (VEGF) as a predictor of recurrence in patients with advanced-stage esophageal squamous cell carcinoma (ESCC) following curative esophagectomy followed by chemotherapy or concurrent radiotherapy. Patients with locally advanced resectable ESCC underwent R0 esophagectomy followed by chemotherapy or concurrent radiotherapy as an adjuvant. Serum VEGF levels in 173 patients, including 57 patients with recurrent disease, and 183 healthy controls were determined using a Luminex assay.

A net-zero emissions strategy for China's power sector using carbon-capture utilization and storage.

Decarbonized power systems are critical to mitigate climate change, yet methods to achieve a reliable and resilient near-zero power system are still under exploration. This study develops an hourly power system simulation model considering high-resolution geological constraints for carbon-capture-utilization-and-storage to explore the optimal solution for a reliable and resilient near-zero power system. This is applied to 31 provinces in China by simulating 10,450 scenarios combining different electricity storage durations and interprovincial transmission capacities, with various shares of abated fossil power with carbon-capture-utilization-and-storage.

CRNDE mediated hnRNPA2B1 stability facilitates nuclear export and translation of KRAS in colorectal cancer.

Development of colorectal cancer (CRC) involves activation of Kirsten rat sarcoma viral oncogene homolog (KRAS) signaling. However, the post-transcriptional regulation of KRAS has yet to be fully characterized. Here, we found that the colorectal neoplasia differentially expressed (CRNDE)/heterogeneous nuclear ribonucleoprotein A2/B1 (hnRNPA2B1) axis was notably elevated in CRC and was strongly associated with poor prognosis of patients, while also significantly promoting CRC cell proliferation and metastasis both in vitro and in vivo.

CLASRP oncogene as a novel target for colorectal cancer.

Clk4-associated serine/arginine-rich protein (CLASRP), an alternative splicing regulator, may be involved in the development and progression of cancer by regulating the activity of the CDC-like kinase (Clk) family. This study explored the biological function of CLASRP in colorectal cancer (CRC). The expression of CLASRP, which is associated with clinicopathological features, was analysed in CRC tissues and paired noncancer tissues by RT-PCR.

Machine-learning-assisted material discovery of oxygen-rich highly porous carbon active materials for aqueous supercapacitors.

Porous carbons are the active materials of choice for supercapacitor applications because of their power capability, long-term cycle stability, and wide operating temperatures. However, the development of carbon active materials with improved physicochemical and electrochemical properties is generally carried out via time-consuming and cost-ineffective experimental processes. In this regard, machine-learning technology provides a data-driven approach to examine previously reported research works to find the critical features for developing ideal carbon materials for supercapacitors.

Transferability evaluation of the deep potential model for simulating water-graphene confined system.

Machine learning potentials (MLPs) are poised to combine the accuracy of ab initio predictions with the computational efficiency of classical molecular dynamics (MD) simulation. While great progress has been made over the last two decades in developing MLPs, there is still much to be done to evaluate their model transferability and facilitate their development. In this work, we construct two deep potential (DP) models for liquid water near graphene surfaces, Model S and Model F, with the latter having more training data.

Antioxidative effect of extract on dextran sulfate sodium-induced ulcerative colitis through activation of the Nrf2 signal.

Context: L. (Blattariae) is used as a treatment for ulcerative colitis (UC) in Chinese traditional medicine.

Objective: To evaluate the antioxidative activity of whole body ethanol extract (PAE) on UC mice and whether glycine and proline could be used for quality control and identification of active PAE components.