A recent study has revealed that the potato glucose 6-phosphate transporter StGPT1, which resides in both chloroplasts and the endoplasmic reticulum (ER), plays a crucial role in defending plants against Phytophthora infestans, the pathogen responsible for late blight. 

Kiwifruit bacterial canker, caused by Pseudomonas syringae pv. actinidiae (Psa), is a devastating disease threatening global kiwifruit production. 

As a green sustainable alternative technology, synthesizing nitrate by electrocatalytic nitrogen oxidation reaction (NOR) can replace the traditional energy-intensive Ostwald process. But low nitrogen fixation yields and poor selectivity due to the high bond energy of the N≡N bond and competition from the oxygen evolution reaction in the electrolyte restrict its application. On the other hand, two-dimensional (2D) PdS₂ as a member in the family of group-10 novel transition metal dichalcogenides (NTMDs) presents the interesting optical and electronic properties due to its novel folded pentagonal structure, but few researches involve to its fabrication and application. Herein, unique imitating growth feature for PdS₂ on different 2D substrates has been firstly discovered for constructing 2D/2D heterostructures by interface engineering. Due to the different exposed chemical groups on the substrates, PdS₂ grows as the imitation to the morphologies of the substrates and presents different thickness, size, shape and the degree of oxidation, resulting in the significant difference in the NOR activity and stability of the obtained composite catalysts. Especially, the thin and small PdS₂ nanoplates with more defects can be obtained by decorating poly(1-vinyl-3-ethylimidazolium bromide) on the 2D substrate, easily oxidized during the preparation process, resulting in the in situ generation of SO₄²⁻, which plays a crucial role in reducing the activation energy of the NOR process, leading to improved efficiency for nitrate production, verified by theoretical calculation. This research provides valuable insights for the development of novel electrocatalysts based on NTMDs for NOR and highlights the importance of interface engineering in enhancing catalytic performance.

Urolithiasis is rising in prevalence, imposing a significant healthcare burden globally. Researchers from China analyzed global health database to reveal increase in total incidence and mortality from urolithiasis over the last 30 years. Age-standardized incidence and mortality rates were higher in males, particularly in countries with low socio-economic development. Notably, China has succeeded in reducing incidence rates of urolithiasis, and insights from their strategies will strengthen measures to reduce the disease burden in vulnerable regions.

Light and ultrasonic mechanical waves in optical fibers are coupled together and affect each other. This phenomenon is important for unique sensors, laser sources, and signal processing. Researchers in Israel examined the generation of ultrasound in an advanced type of fiber, supporting several optical modes. The fiber enables the excitation of wider range of ultrasonic waves, reaching higher frequencies and new forms of symmetry. The results can lead to better laser sources and fiber sensors.

A research team led by Prof. HUANG Qing from the Ningbo Institute of Materials Technology and Engineering of the Chinese Academy of Sciences has developed a new way to "edit" the internal layers of certain advanced materials, called MAX phases, in a breakthrough that could lead to entirely new kinds of two-dimensional (2D) layered materials with valuable technological uses.

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks. Graph neural networks (GNNs) have achieved great success in representation learning on graphs, facilitating various downstream tasks. However, GNNs have several drawbacks such as lacking interpretability, can easily inherit the bias of data and cannot model casual relations. Recently, counterfactual learning on graphs has shown promising results in alleviating these drawbacks. Various approaches have been proposed for counterfactual fairness, explainability, link prediction and other applications on graphs. To facilitate the development of this promising direction, in this survey, researchers categorize and comprehensively review papers on graph counterfactual learning. Researchers divide existing methods into four categories based on problems studied. For each category, they provide background and motivating examples, a general framework summarizing existing works and a detailed review of these works. Researchers point out promising future research directions at the intersection of graph-structured data, counterfactual learning, and real-world applications. To offer a comprehensive view of resources for future studies, researchers compile a collection of open-source implementations, public datasets, and commonly-used evaluation metrics. This survey aims to serve as a “one-stop-shop” for building a unified understanding of graph counterfactual learning categories and current resources.

Radio-photovoltaic cells, as a kind of nuclear battery, have a high energy density but low energy conversion efficiency (ECE). Scientists in China have developed a high-efficiency RPVC using multilayer-stacked GAGG:Ce scintillation waveguides and ⁹⁰Sr radioisotopes, which achieves a record ECE of 2.96%. Remarkably, the cells retain 86.2% of its initial performance after exposure to 50 years of equivalent irradiation at a milliwatt-level output. This breakthrough provides a maintenance-free power solution for extreme environments such as deep-sea exploration and space missions.

A study of 4,257 pneumonia patients identified three clinical phenotypes with distinct outcomes. The use of 80mg equivalent intravenous methylprednisolone treatment can reduce patient mortality in phenotype C. Precision treatment based on phenotypes could optimize therapy.

Sweetness defines the appeal of citrus, and it is the soluble sugars in the pulp that set the tone for flavor.