A Monolithic O-Band Coherent Optical Receiver for Energy-Efficient Links
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Movaghar, Ghazal↗
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A Low-Power Data Link for Stitched Pixel Sensors
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47 OTHER INSTRUMENTATION↗
Optimizing Non-Terrestrial Hybrid RF/FSO Links With Reinforcement Learning: Navigating Through Clouds
In the pursuit of ubiquitous broadband connectivity, there has been a significant shift towards the vertical expansion of communication networks into space, particularly through the exploitation of low Earth orbit (LEO) satellite constellations, which are favored for their relatively low latency. However, this approach faces many challenges that need to be addressed, including atmospheric turbulence, high path loss, and dynamic cloud formations. High-altitude pseudo-satellites (HAPS) have emerged as promising relaying layers between LEO satellites and ground stations, enhancing coverage, latency, and direct terrestrial user connectivity. While radio frequency (RF) bands suffer from congestion and limited bandwidth, free space optical (FSO) communications offer higher data rates, but are susceptible to misalignment and weather-induced signal degradation. To address these challenges, a hybrid RF/FSO approach has been proposed to take advantage of both technologies by dynamic switching between RF and FSO based on propagation channel conditions. This paper introduces a reinforcement learning-based algorithm designed to optimize the trajectory of HAPS, maneuver around cloudy areas, and seamlessly switch between the RF and FSO communication modes to maximize the achievable capacity. The proposed approach aims to maximize system performance by intelligently adapting to environmental conditions and offering a promising solution for next-generation space communication networks.
actor-critic algorithm↗
Canopy Structure Exhibits Linear and Nonlinear Links to Biome‐Level Maximum Light Use Efficiency
Maximum light use efficiency (ε max ) represents a plant's capacity to convert light into carbon during photosynthesis. Although prior studies have explored ε max variations between sunlit and shaded leaves or its temporal ties to canopy structure, the spatial relationship between biome-level ε max (ε biome ) and biome structure remains poorly understood. We analysed data from 320 eddy covariance sites (~855 site-years) with satellite-derived near-infrared reflectance of vegetation (NIRv) and leaf area index (LAI). We introduced NIRvN (NIRv/LAI) to isolate architectural effects from leaf quantity. Site-level ε max was calculated and aggregated by biome to derive ε biome . Results show ε biome rises nonlinearly with NIRv and LAI, saturating at high LAI, with crops and tropical evergreen forests deviating from this trend. Conversely, ε biome decreases linearly with increasing NIRvN, indicating that biomes with greater NIR scattering efficiency exhibit lower ε biome . These results enhance understanding of structural influences on carbon uptake across global biomes.
54 ENVIRONMENTAL SCIENCES↗
Habitat Affinity of Riverine Dissolved Organic Matter Linked to Molecular Traits
Fluxes of organic matter across Earth habitats shape ecosystem function and carbon storage. Yet, it is challenging to predict howthe molecules are preferentially accumulated in specific habitats, that is, the habitat affinities, due to their diverse character-istics. Here, we develop an indicator of compositional-level habitat affinity for dissolved organic matter (DOM) by quantifyingthe aggregated affinities of individual molecules that are over- or under-represented relative to a reference habitat. Applyingthis indicator to 93 paired riverine water-sediment sites, we find that 65.1% of molecules show non-significant habitat affinitiesfor water or sediment and are thermodynamically favorable and susceptible to microbial degradation. Consistently, the habitataffinities of DOM assemblages decrease with lower molecular weights and recalcitrance for waters, and with higher thermody-namic favorability for sediments. These affinities are both reduced by elevated temperatures and anthropogenic pressures, suchas nitrogen loading and land-use change. Our projection of habitat affinities of global riverine DOM shows that regions withintense anthropogenic disturbances or warm climates, such as East Asia, Western Europe, and the Amazon, tend to exhibit loweraffinities. These findings suggest enhanced molecular homogenization between water and sediment habitats is associated withenvironmental changes and underscore the importance of habitat affinities for predicting the potential trajectories of organiccarbon across ecosystems
Cui, Yifan↗
Linking Plant and Microbial Traits to Soil Carbon for Reliable and Resilient Bioenergy Systems
Bioenergy systems in the United States offer a dual opportunity to supply renewable feedstocks while enhancing ecosystem services such as hydrologic regulation, erosion control, and soil carbon (C) storage. National assessments highlight the potential to grow perennial energy crops to improve soil function and ecosystem resilience. Realizing this potential requires understanding the ecological mechanisms that govern how C is added, transformed, and stabilized in soils. Plant traits determine the quantity, depth, and chemistry of organic inputs, while microbial processes—including carbon use efficiency, necromass formation, and trophic interactions—mediate their transformation and partitioning among soil carbon pools. These biological pathways are shaped by soil physical and chemical properties, including aggregation, texture, and mineralogy, and by environmental drivers such as temperature, moisture, and disturbance, leading to context-dependent outcomes across landscapes. Management practices that diversify feedstocks, minimize disturbance, and maintain soil cover can promote both biomass production and C retention, while microbial amendments and rhizosphere engineering offer emerging, but often context-dependent, tools to optimize plant–microbe interactions. Trade-offs between biomass yield and soil carbon storage may arise when systems favor rapid aboveground productivity at the expense of belowground inputs and microbial processing, underscoring the importance of trait combinations that support both functions. Advances in monitoring, reporting, and verification—spanning precision agriculture, remote sensing, and biosensing—are improving predictive capacity through microbial-explicit process models and model–experiment (ModEx) frameworks. By connecting soil, plant, and microbial processes with advances in modeling and biosensing, this review outlines research priorities focused on trait-based parameterization and ModEx integration. These priorities will support the design of bioenergy systems that are both reliable and resilient, enhancing renewable energy production and ecosystem sustainability.
bioenergy systems↗
Linking Domain Structure Evolution at a Grain Boundary to Piezoelectric Response via Nano‐Diffraction
Electric-field-induced domain structure switching in a 1 𝜇m -thick Pb 0.99 (Zr 0.45 Ti 0.55 ) 0.98 Nb 0.02 O 3 (Nb-doped PZT) bicrystal film was characterized in situ via nano-focused synchrotron diffraction. The epitaxial film was deposited on a (100) SrTiO 3 bicrystal substrate. The changes in domain structure were mapped within a 5 𝜇m × 5 𝜇m area at and around an in-plane tilt-type (23.6°) grain boundary with 50 nm spatial resolution. Rocking curves collected at each point of the mapped area provided the ability to reconstruct spatially-varying three-dimensional (3D) reciprocal space maps around the grain boundary. The 3D reciprocal space maps reveal how different tilted 𝑎 -type domain variants interact with the grain boundary as a function of increasing electric field. Initially, a subset of 𝑎 -type domain variants with their polarization vectors largely orthogonal to the grain boundary were found in greater abundance within 570 nm of the grain boundary, possibly due to X-ray beam-induced local increases in the electrical conductivity, but after the coercive field was exceeded, reconfiguration of the ferroelastic domains was observed. The spatially-varying reciprocal space maps also facilitated evaluation of the strain field across the mapped area, along with 𝑑 33,𝑓 . Significant spatial heterogeneity of strain and 𝑑 33,𝑓 are observed, especially at the coercive field, which was attributed to maintaining deformation compatibility and correlated ferroelastic switching.
36 MATERIALS SCIENCE↗
Linking leaf dark respiration to leaf traits and reflectance spectroscopy across diverse forest types
Leaf dark respiration (R dark ), an important yet rarely quantified component of carbon cycling in forest ecosystems, is often simulated from leaf traits such as the maximum carboxylation capacity (V cmax ), leaf mass per area (LMA), nitrogen (N) and phosphorus (P) concentrations, in terrestrial biosphere models. However, the validity of these relationships across forest types remains to be thoroughly assessed. Here, in this study, we analyzed R dark variability and its associations with V cmax and other leaf traits across three temperate, subtropical and tropical forests in China, evaluating the effectiveness of leaf spectroscopy as a superior monitoring alternative. We found that leaf magnesium and calcium concentrations were more significant in explaining cross-site R dark than commonly used traits like LMA, N and P concentrations, but univariate trait–R dark relationships were always weak (r 2 ≤ 0.15) and forest-specific. Although multivariate relationships of leaf traits improved the model performance, leaf spectroscopy outperformed trait–R dark relationships, accurately predicted cross-site R dark (r 2 = 0.65) and pinpointed the factors contributing to R dark variability. Our findings reveal a few novel traits with greater cross-site scalability regarding R dark , challenging the use of empirical trait–R dark relationships in process models and emphasize the potential of leaf spectroscopy as a promising alternative for estimating R dark , which could ultimately improve process modeling of terrestrial plant respiration.
59 BASIC BIOLOGICAL SCIENCES↗
Microbial vitamin biosynthesis links gut microbiota dynamics to chemotherapy toxicity
ABSTRACT Dose-limiting toxicities pose a major barrier to cancer treatment. While preclinical studies show that the gut microbiota influences and is influenced by anticancer drugs, data from patients paired with careful side effect monitoring remains limited. Here, we investigate capecitabine (CAP)-microbiome interactions through longitudinal metagenomic sequencing of stool from 56 advanced colorectal cancer patients. CAP significantly altered the gut microbiome, enriching for menaquinol (vitamin K2) biosynthesis genes. Transposon library screens, targeted gene deletions, and media supplementation revealed that menaquinol biosynthesis protectsEscherichia colifrom drug toxicity. Stool menaquinol gene and metabolite levels were associated with decreased peripheral sensory neuropathy. Machine learning models trained in this cohort predicted toxicities in an independent cohort. Taken together, these results suggest treatment-associated increases in microbial vitamin biosynthesis serve a chemoprotective role for bacterial and host cells. Further, our findings provide a foundation for in-depth mechanistic dissection, human intervention studies, and extension to other cancer treatments. IMPORTANCE Side effects are common during the treatment of cancer. The trillions of microbes found within the human gut are sensitive to anticancer drugs, but the effects of treatment-induced shifts in gut microbes for side effects remain poorly understood. We profiled gut microbes in colorectal cancer patients treated with capecitabine and carefully monitored side effects. We observed a marked expansion in genes for producing vitamin K2 (menaquinone). Vitamin K2 rescued gut bacterial growth and was associated with decreased side effects in patients. We then used information about gut microbes to develop a predictive model of drug toxicity that was validated in an independent cohort. These results suggest that treatment-associated increases in bacterial vitamin production protect both bacteria and host cells from drug toxicity, providing new opportunities for intervention and motivating the need to better understand how dietary intake and bacterial production of micronutrients like vitamin K2 influence cancer treatment outcomes.
Microbiology↗
Sac1 links phosphoinositide turnover to cryptococcal virulence
Cryptococcus neoformans is an environmentally acquired fungal pathogen that causes over 140,000 deaths per year. Cryptococcal infection occurs when infectious particles are deposited into the lung, where they encounter host phagocytic cells. C. neoformans may be engulfed by these phagocytes, an important step of infection that leads to outcomes ranging from termination of infection to cryptococcal dissemination. To study this critical process, we screened approximately 4,700 cryptococcal gene deletion mutants for altered uptake, using primary mouse and human phagocytic cells. Among the hits of these two screens, we identified 93 mutants with perturbed uptake in both systems, as well as others with differences in uptake by only one cell type. We further screened the hits for changes in thickness of the capsule, a protective polysaccharide layer around the cell which is an important cryptococcal virulence factor. The combination of our three screens yielded 45 mutants, including one lacking the phosphatidylinositol-4-phosphate phosphatase Sac1. In this work, we implicate Sac1 in both host cell uptake and capsule production. We found that sac1 mutants exhibit lipid trafficking defects, reductions in secretory system function, and changes in capsule size and composition. Many of these changes occur specifically in tissue culture media, highlighting the role of Sac1 phosphatase activity in responding to the stress of host-like conditions. Overall, these findings show how genome-scale screening can identify cellular factors that contribute to our understanding of cryptococcal biology and demonstrate the role of Sac1 in determining fungal virulence.
59 BASIC BIOLOGICAL SCIENCES↗
Elucidation of a bacterial pathway for catabolism of the β–β-linked dilignol pinoresinol
Monolignol-derived dimers containing β–β linkages are synthesized by vascular plants and can be released during lignin depolymerization. In this work, we isolated a bacterium, Novosphingobium rhizosphaerae LY, that grows with the β–β lignan (+)-pinoresinol as a sole growth substrate. Sequence analysis suggested that this strain encodes a broad range of pathways for assimilation of aromatic monomers as well as one enzyme implicated in pinoresinol catabolism but lacks other known pathways for aromatic dimer catabolism. We constructed a genome-wide barcoded transposon library and identified genes required for pinoresinol catabolism. Using feeding studies, compound isolation, targeted synthesis, and analysis of purified enzymes, we elucidated the biochemical intermediates and reaction pathway involved in pinoresinol catabolism. We demonstrated that the first enzymatic reaction is the reductive cleavage of a furan ring in (±)-pinoresinol with retention of configuration to yield lariciresinol. We additionally confirmed that the final pathway enzyme, PinU, is related to lignostilbene dioxygenases and oxidatively cleaves a diguaiacylbutadiene intermediate to yield vanillin and coniferaldehyde. Finally, based on the enzyme characterization, we demonstrated that the strain can grow with a second β–β lignan, (–)-syringaresinol, as a sole growth substrate. In combination, these results demonstrate a new biocatalytic route for transforming a widely occurring group of plant phenylpropanoid natural products.
Novosphingobium↗
RefAHL: a curated quorum sensing reference linking diverse LuxI-type signal synthases with their acyl-homoserine lactone products
Some bacteria use acyl-homoserine lactone (AHL) signals in quorum sensing, a type of cell-cell communication. Here, we present “RefAHL,” an updated, curated collection of LuxI-type AHL synthases with their AHL products and associated metadata. RefAHL is publicly available as a community resource to help catalog LuxI-type diversity encoded in (meta) genomic data.
59 BASIC BIOLOGICAL SCIENCES↗
Metagenomic clustering links specific metabolic functions to globally relevant ecosystems
ABSTRACT Metagenomic sequencing has advanced our understanding of biogeochemical processes by providing an unprecedented view into the microbial composition of different ecosystems. While the amount of metagenomic data has grown rapidly, simple-to-use methods to analyze and compare across studies have lagged behind. Thus, tools expressing the metabolic traits of a community are needed to broaden the utility of existing data. Gene abundance profiles are a relatively low-dimensional embedding of a metagenome’s functional potential and are, thus, tractable for comparison across many samples. Here, we compare the abundance of KEGG Ortholog Groups (KOs) from 6,539 metagenomes from the Joint Genome Institute’s Integrated Microbial Genomes and Metagenomes (JGI IMG/M) database. We find that samples cluster into terrestrial, aquatic, and anaerobic ecosystems with marker KOs reflecting adaptations to these environments. For instance, functional clusters were differentiated by the metabolism of antibiotics, photosynthesis, methanogenesis, and surprisingly GC content. Using this functional gene approach, we reveal the broad-scale patterns shaping microbial communities and demonstrate the utility of ortholog abundance profiles for representing a rapidly expanding body of metagenomic data. IMPORTANCE Metagenomics, or the sequencing of DNA from complex microbiomes, provides a view into the microbial composition of different environments. Metagenome databases were created to compile sequencing data across studies, but it remains challenging to compare and gain insight from these large data sets. Consequently, there is a need to develop accessible approaches to extract knowledge across metagenomes. The abundance of different orthologs (i.e., genes that perform a similar function across species) provides a simplified representation of a metagenome’s metabolic potential that can easily be compared with others. In this study, we cluster the ortholog abundance profiles of thousands of metagenomes from diverse environments and uncover the traits that distinguish them. This work provides a simple to use framework for functional comparison and advances our understanding of how the environment shapes microbial communities.
54 ENVIRONMENTAL SCIENCES↗
Data-Driven Clustering and Classification of Outage Patterns with Insights into their Links to Extreme Events
At a global level extreme events have increased in both scale and impact. These events have the potential to affect the electrical grid infrastructure and cause a wide range of outages, which can lead to a disruption in daily patterns, cost millions of dollars and also the loss of life. Currently, to track these outage events there have been various approaches developed ranging from regional to national level quantifications for what defines an outage. However, this variation in methods can potentially lead to subjective decision-making and a lack of proper management in relation to the event. While previous work has made strides in determining spatio-temporal patterns, minimal attention has been given to the type and number of outages an area may be exposed to. The differences in incurred cost and the overall severity of an event between a transformer box malfunction and a hurricane are drastic, and by finding historical signals, we can allow for more efficient management, potentially saving lives and millions of dollars. Here, we leverage unsupervised machine learning techniques to delineate outage patterns among 22 counties within the United States and find that there are clear, segregated clusters (0.93 silhouette) of data which are related by event behavior and underlying cause. This finding will allow for energy stakeholders, policy makers, and researchers to gain a deeper understanding of the extent and severity of historic events and to better prepare for electrical grid infrastructure planning and management.
Koob, Benjamin [ORNL]↗
Lithium-Ion Batteries with Lithium Manganese Iron Phosphate Cathodes and Lithium Titanate Anodes: Linking Electrode Dynamics to Cell Performance
This study examines the electrochemical performance, impedance behavior, and aging mechanisms of lithium-ion cells pairing lithium manganese iron phosphate (LiMn 0.6 Fe 0.4 PO 4 , LMFP64) cathodes with lithium titanate (Li 4 Ti 5 O 12 , LTO) anodes. LMFP64 half-cells display distinct Fe and Mn redox plateaus at ∼3.5 and ∼4.1 V, respectively, and deliver excellent rate capability. Three-electrode measurements show that LMFP64 dominates cell impedance, which changes sharply across the Fe–Mn redox transition and decreases with increasing temperature (30 °C–50 °C). Voltage hysteresis arises mainly from the cathode, with higher C-rates shortening redox plateaus and broadening the transition region. Elevated temperature lowers impedance, especially near the Mn-redox and transition regions, but accelerates capacity fade. Post-cycling analyses of electrodes confirm structural stability of LMFP64 and indicate loss of lithium inventory (LLI) as the source of capacity fade. This LLI causes potential slippage between the LMFP64 and LTO electrodes, which decreases the Fe-redox plateau width. Long-term cycling highlights the critical role of electrode overhang: cathode overhang mitigates capacity fade by buffering lithium loss, whereas anode overhang cells experience faster capacity decline due to uncompensated lithium depletion. These results clarify LMFP64/LTO battery impedance evolution, thermal effects, and degradation pathways and provide insights for their applications in electric vehicles.
Area Specific Impedance↗
YAP1 Dysfunction Promotes Molecular Properties Linked to Breast Cancer Susceptibility
YAP1 is a cotranscription factor that promotes malignant and stem cell properties in cancer. We previously found that YAP1 dysregulation is associated with aging in human mammary epithelia. With increased age, YAP1 expression changes in luminal epithelial cells, the prospective breast cancer cell of origin. Because age is a significant risk factor for breast cancer, we tested whether YAP1 dysregulation acted early in cancer progression by conferring cellular states associated with increased cancer susceptibility. In this study, we find that with increased age and genetic risk for developing cancer, human breast tissues showed significantly increased YAP1 expression, and cultured primary human mammary epithelial cells (HMEC) showed significantly increased expression of both YAP1 and its transcriptional targets. Increased YAP1 expression in cultured HMEC induced gene expression changes associated with increased cancer susceptibility, such as genes associated with stem cell states, increased telomerase activity, breast cancer progression, and increased age and genetic breast cancer risk. Furthermore, overexpression of YAP1 in post-stasis HMEC—finite lifespan cells that have bypassed a retinoblastoma-mediated senescence barrier—promoted properties related to increased growth potential. We found that YAP1 dysregulation in finite epithelial cells allows for access to gene programs and functions that are typically thought to be restricted to stem cells. We hypothesize that YAP1 acts early in breast cancer progression, long before the development of a tumor, to impose cancer-susceptible molecular states.
YAP1↗
Identifying spatiotemporal patterns in opioid vulnerability: investigating the links between disability, prescription opioids and opioid-related mortality
Background: The opioid crisis remains one of the most daunting and complex public health problems in the United States. This study investigates the national epidemic by analyzing vulnerability profiles of three key factors: opioid-related mortality rates, opioid prescription dispensing rates, and disability rank ordered rates. Methods: This study utilizes county level data, spanning the years 2014 through 2020, on the rates of opioid-related mortality, opioid prescription dispensing, and disability. To successfully estimate and predict trends in these opioid-related factors, we augment the Kalman Filter with a novel spatial component. To define opioid vulnerability profiles, we create heat maps of our filter’s predicted rates across the nation’s counties and identify the hotspots. In this context, hotspots are defined on a year-by-year basis as counties with rates in the top 5% nationally. Results: Our spatial Kalman filter demonstrates strong predictive performance. From 2014 to 2018, these predictions highlight consistent spatiotemporal patterns across all three factors, with Appalachia distinguished as the nation’s most vulnerable region. Starting in 2019 however, the dispensing rate profiles undergo a dramatic and chaotic shift. Conclusions: The initial primary drivers of opioid abuse in the Appalachian region were likely prescription opioids; however, it now appears that abuse is sustained by illegal drugs. Additionally, we find that the disabled subpopulation may be more at risk of opioid-related mortality than the general population. Public health initiatives must extend beyond controlling prescription practices to address the transition to and impact of illicit drug use.
60 APPLIED LIFE SCIENCES↗
Shaping with water: linking moisture perception to development in plant roots
Water is the most limiting resource for plant growth and development. Heterogeneity in the environmental distribution of water requires plants to direct root growth toward water and to avoid investing resources in areas that lack water. Roots use hydrosignaling pathways—hydrotropism, hydropatterning, and xerobranching—to sense and respond to water availability. While molecular mechanisms of water perception remain unclear, recent studies suggest that organ-level processes using proxies like ethylene help detect spatial water patterns. This review summarizes advances in hydrosignaling and identifies key knowledge gaps to address how plants sense water. Understanding these processes will guide strategies to improve root water capture for sustainable agriculture.
59 BASIC BIOLOGICAL SCIENCES↗