Accurately predicting how terrestrial ecosystems will respond to global change is essential for assessing and projecting the land carbon sink, and with it the pace of future climate change. It has become one of the central problems in global change science, yet neither of the field's two main tools can solve this endeavor on its own. Field experiments that deliberately manipulate global change drivers (e.g., CO₂ concentration) supply direct empirical evidence, but cover only a few years and a limited number of experimental sites. Process-based models that simulate how ecosystems work can project across the globe and centuries ahead, but rest on simplified, sometimes competing assumptions that leave their forecasts uncertain. The emerging solution is to couple the two, an approach known as data-model integration, in which experiments test and refine the assumptions inside models, while models in turn guide the design of more informative experiments.

A Florida State University paleoclimatologist led the creation of a global database hosting thousands of seawater isotope measurements collected over almost 50 years that will aid scientists in generating more accurate climate reconstructions and predictions.

The statistical analysis, based on the Wilcoxon test with a significance level of p < 0.05, confirmed substantial improvements across all participant groups. Overall, the ability to distinguish between hypocenter and epicenter increased by 45.39%; understanding of seismic magnitude improved by 39.01%; and the visual identification of structural vulnerabilities increased between 25% and 38%, with moderate to large effect sizes.

γ-Aminobutyric acid type A receptors (GABAARs) are the principal inhibitory neurotransmitter receptors in the mature central nervous system (CNS) that play essential roles in regulating neuronal excitability. The GABRA1 gene, which encodes the α1 subunit of the GABAARs, represents a critical nexus in CNS inhibitory neurotransmission. Pathogenic missense variants within this gene are predominantly associated with a spectrum of neurodevelopmental disorders, such as epilepsy, developmental delay, and neurodevelopmental encephalopathies. These pathogenic variants typically alter receptor function bidirectionally, resulting in either a gain-of-function (GOF) or a loss-of-function (LOF) phenotype.

The presence of tertiary lymphoid structures (TLSs)—ectopic lymphoid tissues that develop within tumors—has recently emerged as a critical biomarker for predicting favorable responses to cancer immunotherapy. However, finding effective therapeutic strategies to actively induce the formation of these organized structures has remained a significant clinical hurdle. While Interleukin-7 (IL-7) is a vital cytokine known to support T cell survival and lymphoid organogenesis, its short half-life severely limits its therapeutic application. 

Semitransparent thin-film photovoltaics (PV) have been increasing popular for urban structures, vehicles, and applications requiring visible transparency. However, these materials suffer from reduced light absorption, owing to limited absorber volume, leading to low efficiency. In a new study, researchers utilized geometric optics principles to create a novel microprism sheet that leverages light trapping effect to significantly enhance light absorption of thin-film PV sheets.

Korean researchers have developed, for the first time in Korea, a 200Gbps-class photodetector device that can be used in hyperscale AI data centers and 5G/6G mobile communications infrastructure. This technology enables ultrahigh-speed data reception at a level capable of transmitting five 5GB full HD movies per second. Electronics and Telecommunications Research Institute (ETRI) announced that it has developed a photodetector device capable of processing 200Gbps-class optical signals per channel. A photodetector is a key semiconductor component that converts optical signals into electrical signals and is an essential element that determines data reception performance in data centers and communication networks.