The nitrogen conversion underpins ecosystem stability, chemical synthesis, and energy production. However, anthropogenic perturbations and energy-intensive industrial catalytic processes underscore the urgent need for sustainable nitrogen conversion. Microbial nitrogen conversion encompasses diverse metabolic pathways but remains challenging to regulate. Biophotoelectrochemical (BPEC) systems, which integrate photosensitizers with biocatalysts, provide a platform for coupling solar energy with biological nitrogen transformations, enabling external modulation of reaction pathways and selectivity. Here we systematically summarize recent advances in BPEC systems for nitrogen conversion, with emphasis on the construction and applications of photoelectrode–enzyme/cell hybrids and nanoparticle–enzyme/cell hybrids. Beyond widely studied processes such as nitrogen fixation, denitrification, and anaerobic ammonium oxidation (anammox), we also highlight the emerging and less-explored pathways, including dissimilatory nitrate reduction to ammonium (DNRA), direct ammonium oxidation (dirammox), complete ammonia oxidation (comammox), partial denitrification, and nitrification, within an integrative framework. Particular attention is given to emerging biological nitrogen oxidation routes and the potential role of photocatalytic oxidation in expanding BPEC functionality. Furthermore, we critically examine core challenges in BPEC systems, including interfacial electron transfer, system stability, sacrificial agent dependence, material selection, and detection reliability. Finally, future research directions are outlined to guide the development of BPEC systems toward efficient and sustainable nitrogen cycle regulation, with implications for environmental remediation and green energy synthesis.
The relationship between the boreal summer Atlantic Niño and subsequent winter El Niño-Southern Oscillation (ENSO) has strengthened in recent decades, but the underlying mechanism remains unclear. In this study, we identified tropical Atlantic and Pacific sea surface temperature (SST) gradients as the key drivers of the summer Atlantic Niño-winter ENSO connection. In detail, zonal SST gradients over the tropical Atlantic, driven by wind-evaporation-SST feedback, regulate the Atlantic Niño-ENSO connection by modulating the cross-basin Walker circulation between the tropical western Atlantic and eastern Pacific. Under weak zonal SST gradients, the Gill-Matsuno-type response to the Atlantic Niño exhibits stronger ascending motion over the tropical western Atlantic than under strong gradient conditions. The meridional SST gradients over the tropical eastern Pacific enhance anomalous descent that helps to establish the cross-basin Walker circulation. Consequently, the enhanced Pacific Walker circulation contributes to the development of La Niña and strengthens the Atlantic Niño-ENSO connection. Model sensitivity experiments confirm this mechanism. This study has identified new drivers of tropical Atlantic-Pacific cross-basin linkages that have significant implications for ENSO prediction.
RR Lyrae stars are essential standard candles for distance measurements in the Milky Way and nearby galaxies. Traditional estimates rely on the Period–Absolute Magnitude–Metallicity relation but are limited by uncertainties in metallicity determinations. We present a deep learning approach that directly predicts absolute magnitudes from RRab and RRc light curves, eliminating the need for metallicity estimates. Our model achieves validation precisions of 0.053 mag and 0.036 mag (approximately 2.5% and 1.7% in distance) for individual RRab and RRc stars, respectively. Tests on globular clusters yield typical distance precisions of 1.0% for RRab and 1.7% for RRc stars. For the benchmark systems, combining the RRab- and RRc-based models yields distance moduli of 18.498±0.001stat±0.018sys mag for the Large Magellanic Cloud and 19.564±0.003stat±0.019sys mag for the Sculptor dwarf spheroidal galaxy. These measurements are in excellent agreement with previous results, achieve a distance precision of approximately 1%, and represent a 1.8-fold improvement over traditional RR Lyrae calibration relations. Our approach showcases the ability of AI to directly extract key physical parameters from complex, information-rich light curves, resolve degeneracies, and scale to broader applications
Pharmaceuticals have played a major role in supporting human and animal health over the last century. As a consequence of this use, pharmaceuticals are now ubiquitous in the environment and are recognized as organic pollutants affecting multiple non-target organisms. Pollution by pharmaceuticals can impact organisms directly or indirectly through food-chain-mediated effects, affecting terrestrial, freshwater, and marine ecosystems. Moreover, antimicrobial residues and psychotropic drugs, including antidepressants, are known to facilitate the evolution and transmission of resistant microorganisms in the environment, affecting the health of humans, animals, and ecosystems. One important step in tackling this global challenge is to raise awareness about the sources, transmission routes, environmental risks, and impacts of pharmaceuticals. Here, we aim to disentangle knowns and unknowns of pharmaceuticals related to environmental sources, occurrence, behavior, exposure, and toxicity; possible treatment technologies; bioremediation; and implementation of environmental policies. Therefore, in this review, we present a synthesis of current knowledge regarding pharmaceutical pollution and provide recommendations for citizens, scientists, and governments to improve the environmental management of pharmaceuticals, innovate mitigation technologies, and inform global and local policies, using a “One Health” framework.
