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Photoconvertible fluorescent proteins (pcFPs) have enabled exquisite images of cellular structures due to their genetic encodability and red-shifted emission with high brightness, hence receiving increased traction in the field. However, the red form of Kaede-like pcFPs after photoconversion remains underexplored. We implemented ultrafast electronic and vibrational spectroscopies on the red Kaede chromophore in solution vs the protein pocket of the least-evolved ancestor (LEA, a Kaede-like green-to-red pcFP) to gain crucial insights into the photophysical processes of the chromophore. The measured fluorescence quantum yield (FQY) values were correlated with ultrafast dynamics to reveal that hydrogen-bonding interactions with the solvent can quench the excited-state Kaede in solution. A viscosity-dependent sub-ps decay indicates nonradiative relaxation involving swift chromophore conformational motions. Femtosecond transient absorption and stimulated Raman spectroscopy (FSRS) reveal an additional ∼1 ps decay of the photoconverted red form of LEA that is absent in green LEA before photoconversion. Transient structural dynamics from FSRS elucidate this decay to involve the phenolate and imidazolinone ring twists that are implicated during cis → trans isomerization and on → off photoswitching in phototransformable fluorescent proteins (FPs). Compared to green-emitting species, the FQY of red LEA (∼0.58) and many other red FPs are often reduced, limiting their applications in modern bioimaging techniques. By shining more light on the often overlooked photoconverted form of pcFPs with ultrafast spectroscopies, we envision such essential mechanistic insights to enable a bottom-up approach for rationally improving the brightness of red-emitting LEA and many other controllable bioprobes, including FPs. 

With the growing emphasis on sustainability, criticality, and availability in materials research, providing actionable information about mineral commodities is crucial for informed decision-making and strategic planning by researchers, policy makers, and industry stakeholders. While the United States Geological Survey (USGS) offers valuable information on mineral-commodity summaries, their unstructured nature makes analysis challenging. To address this, we present a comprehensive data-analytics application () that processes the past 10 years of USGS mineral-commodity summaries into actionable insights. The application offers country-specific insights into global elemental production and reserves, along with quantitative metrics such as the Herfindahl-Hirschman index (HHI) to evaluate market concentration, identifying risks and opportunities in resource availability. It also features an artificial-intelligence assistant powered by a large language model (LLM) and a retrieval–augmented generation (RAG) system, enabling users to query various aspects of raw materials, including reserves, production, market share, usage, price, substitutes, recycling, and more. We evaluated multiple open-source LLMs for the RAG task and selected the best-performing model, , to implement in the system. This application provides valuable support for material scientists in assessing sustainability, criticality, and market risks, thereby aiding in the development of new materials. We demonstrate its application in energy materials, and by describing the application architecture and providing open access to the code, we aim to enable data-driven advancements in materials research. 

The Front Cover illustrates ultrafast spectroscopic insights into the photoexcited energy relaxation pathways of St. John's wort-derived fluorescent photosensitizer hypericin in solution. The bidirectional excited-state intramolecular proton transfer (ESIPT) gains prominence after UV excitation with enhanced photoprotection in a “proton pachinko”, whereas visible excitation results in more phototoxicity. More information can be found in the Research Article by C. Fang and co-workers (DOI: 10.1002/chem.202500639). Cover design by S. Johnson and C. Fang. 

Biophysical Lagrangian particle tracking models used to predict larval transport and dispersal are potentially sensitive to input parameters. Here we test the effects of four common input parameters (release interval, number of particles, diffusion, and release depth) for a 2D particle tracking model in the North Central Pacific Ocean. We evaluated the effects on modeled larval transport (particle movement) and dispersal (import) into the Hawaiian Archipelago from eight different regions for a shallow reef organism. Model results were sensitive to all input parameters to varying degrees across the planktonic larval duration/settlement windows and output metrics (transport vs. dispersal) tested. Variation in larval transport pathways 180 days after release was only evident when evaluating depth of release. In contrast, larval transport at 30 days post release did not vary when testing depth of release. Larval dispersal was not different for shorter settlement windows (30 days) regardless of the parameter tested. Occasional connections between distant archipelagos (e.g., Kiritimati, Okinawa, Wake) only occurred when larval duration was at its maximum (180 days), but these long- distance connections were also variable with depth of release. Out of the four parameters tested, changes in release depth resulted in the most significant differences for larval transport and had inconsistent connections for larval dispersal. These outcomes emphasize the importance of choosing a depth layer in future modeling studies. Because factors that affect larval depth distribution, such as spawning depth, buoyancy changes, and swimming behavior, are typically unknown for many taxa, future research should focus on field sampling to determine these in situ behaviors for better parameterization of models. 

Drift and gene flow affect genetic diversity. Given that the strength of genetic drift increases as population size decreases, management activities have focused on increasing population size through preserving habitats to preserve genetic diversity. Few studies have empirically evaluated the impacts of drift and gene flow on genetic diversity.Kryptolebias marmoratus, henceforth ‘rivulus’, is a small killifish restricted to fragmented New World mangrove forests with gene flow primarily associated with ocean currents. Rivulus form distinct populations across patches, making them a well-suited system to test the extent to which habitat area, fragmentation and connectivity are associated with genetic diversity. Using over 1000 individuals genotyped at 32 microsatellite loci, high-resolution landcover data and oceanographic simulations with graph theory, we demonstrate that centrality (connectivity) to the metapopulation is more strongly associated with genetic diversity than habitat area or fragmentation. By comparing models with and without centrality standardized by the source population’s genetic diversity, our results suggest that metapopulation centrality is critical to genetic diversity regardless of the diversity of adjacent populations. While we find evidence that habitat area and fragmentation are related to genetic diversity, centrality is always a significant predictor with a larger effect than any measure of habitat configuration. 

Abstract Here, four MOFs, namely Sc-TBAPy, Al-TBAPy, Y-TBAPy, and Fe-TBAPy (TBAPy: 1,3,6,8-tetrakis(p-benzoic acid)pyrene), were characterized and evaluated for their ability to remediate glyphosate (GP) from water. Among these materials, Sc-TBAPy demonstrates superior performance in both the adsorption and degradation of GP. Upon light irradiation for 5 min, Sc-TBAPy completely degrades 100% of GP in a 1.5 mM aqueous solution. Femtosecond transient absorption spectroscopy reveals that Sc-TBAPy exhibits enhanced charge transfer character compared to the other MOFs, as well as suppressed formation of emissive excimers that could impede photocatalysis. This finding was further supported by hydrogen evolution half-reaction (HER) experiments, which demonstrated Sc-TBAPy’s superior catalytic activity for water splitting. In addition to its faster adsorption and more efficient photodegradation of GP, Sc-TBAPy also followed a selective pathway towards the oxidation of GP, avoiding the formation of toxic aminomethylphosphonic acid observed with the other M³⁺-TBAPy MOFs. To investigate the selectivity observed with Sc-TBAPy, electron spin resonance, depleted oxygen conditions, and solvent exchange with D₂O were employed to elucidate the role of different reactive oxygen species on GP photodegradation. The findings indicate that singlet oxygen (¹O₂) plays a critical role in the selective photodegradation pathway achieved by Sc-TBAPy.