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This study uses large eddy simulations to investigate nutrient transport and uptake in suspended macroalgal farms. Various farm configurations and oceanic forcing conditions are examined, with the farm base located near the nutricline depth. We introduce the Damkohler number Da to quantify the balance between nutrient consumption by macroalgae uptake and supply by farm‐enhanced nutrient transport. Most cases exhibit low Da, indicating that farm‐generated turbulence drives sufficient upward nutrient fluxes, supporting macroalgae growth. High Da and starvation may occur in fully grown farm blocks, a configuration that generates the weakest turbulence, particularly when combined with densely planted macroalgae or weak flow conditions. Flow stagnation within the farm due to macroalgae drag may constrain the uptake efficiency and further increase the starvation risk. Mitigation strategies involve timely harvesting, avoiding dense macroalgae canopies, and selecting farm locations with robust ocean currents and waves. This study provides insights for sustainable macroalgal farm planning. Plain Language Summary: Offshore macroalgal farming has been proposed as a sustainable strategy for carbon sequestration, biofuel production, food supply, and bioremediation. However, challenges arise as macroalgal farms are typically suspended above the nutricline and may thus deplete the existing nutrient inventory near the sea surface. In this study, large eddy simulations reveal that suspended farms can generate intense turbulence and drive upward nutrient fluxes from below the farm base. Various farm simulations are conducted, and in most cases the farm‐generated turbulence is indicated to provide sufficient nutrient fluxes to support macroalgae growth. This presents a self‐sustaining solution for nutrient supply through passive entrainment. To mitigate the risk of farm starvation, we propose strategies such as timely harvesting, avoiding dense macroalgae canopies, and selecting farm locations with robust ocean currents and waves. Key Points: Suspended macroalgal farms can enhance turbulence and drive upward nutrient fluxes from below the farm base to prevent starvationThe Damkohler number, comparing nutrient transport with uptake by macroalgae, can be used to predict nutrient availability in the farmFarming strategies are proposed such as timely harvesting and selecting locations with a shallow nutricline and robust currents and waves [ABSTRACT FROM AUTHOR]

Chronic mountain sickness is a maladaptive syndrome that affects individuals living permanently at high altitude and is characterized primarily by excessive erythrocytosis (EE). Recent results concerning the impact of EE in Andean highlanders on clotting and the possible promotion of hypercoagulability, which can lead to thrombosis, were contradictory. We assessed the coagulation profiles of Andeans highlanders with and without excessive erythrocytosis (EE+ and EE−). Blood samples were collected from 30 EE+ and 15 EE− in La Rinconada (Peru, 5100–5300 m a.s.l.), with special attention given to the sampling pre‐analytical variables. Rotational thromboelastometry tests were performed at both native and normalized (40%) haematocrit using autologous platelet‐poor plasma. Thrombin generation, dosages of clotting factors and inhibitors were measured in plasma samples. Data were compared between groups and with measurements performed at native haematocrit in 10 lowlanders (LL) at sea level. At native haematocrit, in all rotational thromboelastometry assays, EE+ exhibited hypocoagulable profiles (prolonged clotting time and weaker clot strength) compared with EE− and LL (all P < 0.01). At normalized haematocrit, clotting times were normalized in most individuals. Conversely, maximal clot firmness was normalized only in FIBTEM and not in EXTEM/INTEM assays, suggesting abnormal platelet activity. Thrombin generation, levels of plasma clotting factors and inhibitors, and standard coagulation assays were mostly normal in all groups. No highlanders reported a history of venous thromboembolism based on the dedicated survey. Collectively, these results indicate that EE+ do not present a hypercoagulable profile potentially favouring thrombosis. What is the central question of this study?Are Andean highlanders with excessive erythrocytosis (EE+) exhibiting a hypercoagulable profile compared with highlanders without erythrocytosis (EE−) and lowlanders (LL)?What is the main finding and its importance?Despite normal plasma coagulation (thrombinography and levels of clotting factors and inhibitors), EE+ exhibited a hypocoagulable rotational thromboelastometry profile (prolonged clotting time and weaker clot strength) compared with EE− and LL. In EE+, haematocrit normalization at 40% corrected maximal clot firmness in rotational thromboelastometry FIBTEM tests, but not in EXTEM and INTEM tests, suggesting that platelets play a role in the native hypocoagulable profile. [ABSTRACT FROM AUTHOR]

The concept of sustainable consumption has gained significant attention in international policy discussions. In order to achieve sustainable consumption, it is essential to thoroughly comprehend the underlying causes of current unsustainable consumption patterns and the associated challenges in transitioning to more sustainable practices. This research, employing perspectives from international political economy and psychology, elucidates that unsustainable consumption is rooted in a combination of systemic and individual factors. Systemic factors encompass unequal exchange relations, lack of efficient telecoupling framework, political and ecological trade‐off dilemma. Individual factors include unsatisfied needs, insufficient environmental concern, and low self‐efficacy. Drawing upon these findings, this study presents a comprehensive set of macro and micro‐level policy recommendations for achieving sustainable consumption and a more equitable and sustainable future. [ABSTRACT FROM AUTHOR]

Formulas containing intact cow milk protein are appropriate alternatives when human milk (HM) is not feasible. However, for babies with a physician‐diagnosed cow milk protein allergy (CMPA), hydrolyzed formulas are needed. We conducted a 3‐month, open‐label, nonrandomized concurrent controlled trial (ChiCTR2100046909) between June 2021 and October 2022 in Qingdao City, China. In this study, CMPA toddlers were fed with a partially hydrolyzed formula containing synbiotics (pHF, n = 43) and compared with healthy toddlers fed a regular intact protein formula (IF, n = 45) or HM (n = 21). The primary endpoint was weight gain; the secondary endpoints were changes in body length and head circumference of both CMPA and healthy toddlers after 3‐month feeding; and the exploratory outcomes were changes in gut microbiota composition. After 3 months, there were no significant group differences for length‐for‐age, weight‐for‐age, or head circumference‐for‐age Z scores. In the gut microbiota, pHF feeding increased its richness and diversity, similar to those of IF‐fed and HM‐fed healthy toddlers. Compared with healthy toddlers, the toddlers with CMPA showed an increased abundance of phylum Bacteroidota, Firmicutes, class Clostridia, and Bacteroidia, and a decreased abundance of class Negativicutes, while pHF feeding partly eliminated these original differences. Moreover, pHF feeding increased the abundance of short‐chain fatty acid producers. Our data suggested that this pHF partly simulated the beneficial effects of HM and shifted the gut microbiota of toddlers with CMPA toward that of healthy individuals. In conclusion, this synbiotic‐containing pHF might be an appropriate alternative for toddlers with CMPA. [ABSTRACT FROM AUTHOR]

Redox–enzyme‐mediated electrochemical processes such as hydrogen production, nitrogen fixation, and CO2 reduction are at the forefront of the green chemistry revolution. To scale up, the inefficient two‐dimensional (2D) immobilization of redox enzymes on working electrodes must be replaced by an efficient dense 3D system. Fabrication of 3D electrodes was demonstrated by embedding enzymes in polymer matrices. However, several requirements, such as simple immobilization, prolonged stability, and resistance to enzyme leakage, still need to be addressed. The study presented here aims to overcome these gaps by immobilizing enzymes in a supramolecular hydrogel formed by the self‐assembly of the peptide hydrogelator fluorenylmethyloxycarbonyl‐diphenylalanine. Harnessing the self‐assembly process avoids the need for tedious and potentially harmful chemistry, allowing the rapid loading of enzymes on a 3D electrode under mild conditions. Using the [FeFe] hydrogenase enzyme, high enzyme loads, prolonged resistance against electrophoresis, and highly efficient hydrogen production are demonstrated. Further, this enzyme retention is shown to arise from its interaction with the peptide nanofibrils. Finally, this method is successfully used to retain other redox enzymes, paving the way for a variety of enzyme‐mediated electrochemical applications. [ABSTRACT FROM AUTHOR]

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The feasibility of different options to reduce the risks of climate change has engaged scholars for decades. Yet there is no agreement on how to define and assess feasibility. We define feasible as "do‐able under realistic assumptions." A sound feasibility assessment is based on causal reasoning; enables comparison of feasibility across climate options, contexts, and implementation levels; and reflexively considers the agency of its audience. Global climate scenarios are a good starting point for assessing the feasibility of climate options since they represent causal pathways, quantify implementation levels, and consider policy choices. Yet, scenario developers face difficulties to represent all relevant causalities, assess the realism of assumptions, assign likelihood to potential outcomes, and evaluate the agency of their users, which calls for external feasibility assessments. Existing approaches to feasibility assessment mirror the "inside" and the "outside" view coined by Kahneman and co‐authors. The inside view considers climate change as a unique challenge and seeks to identify barriers that should be overcome by political choice, commitment, and skill. The outside view assesses feasibility through examining historical analogies (reference cases) to the given climate option. Recent studies seek to bridge the inside and the outside views through "feasibility spaces," by identifying reference cases for a climate option, measuring their outcomes and relevant characteristics, and mapping them together with the expected outcomes and characteristics of the climate option. Feasibility spaces are a promising method to prioritize climate options, realistically assess the achievability of climate goals, and construct scenarios with empirically‐grounded assumptions. This article is categorized under:Climate, History, Society, Culture > Disciplinary PerspectivesAssessing Impacts of Climate Change > Representing UncertaintyThe Carbon Economy and Climate Mitigation > Decarbonizing Energy and/or Reducing Demand [ABSTRACT FROM AUTHOR]

In this paper, the formulation, calibration, and validation of hybrid and coupled models for the design of upflow anaerobic filters in multiple separated stages were developed for organic matter removal from sanitary landfill leachates. Three novelties were presented, the type of reactor, design models, and kinetic coefficients. The upflow anaerobic filters were separated into two and three stages identified as UAF‐2SS (DI‐FAFS, in Spanish) and UAF‐3SS (TRI‐FAFS, in Spanish). The formulation, calibration, and validation of mathematical structures of hybrid models and five coupled models are proposed for each reactor. The hybrid models are based on the law of mass conservation, with the organic matter transformation component within the UAF‐2SS and UAF‐3SS reactors, being estimated from empirical equations that have been tested in aerobic culture reactors, adapted to the experimental factors, including among these, those under a non‐stationary—advective conditions based on Velz's Law, Phelps's Law, and Monod's equation. The coupled models combine the components of the molecular transport by biosorption and molecular diffusion processes, with adaptations of the Stack's equation and Fick's Law, as well as transformation of organic substrates by biomass, whose kinetic coefficients contribute to explain the fraction, in which, the processes of mobility and biochemical transformation of the organic matter are occurring in the biomass within the bioreactors. [ABSTRACT FROM AUTHOR]

Phytoplankton growth is controlled by multiple environmental drivers, which are all modified by climate change. While numerous experimental studies identify interactive effects between drivers, large‐scale ocean biogeochemistry models mostly account for growth responses to each driver separately and leave the results of these experimental multiple‐driver studies largely unused. Here, we amend phytoplankton growth functions in a biogeochemical model by dual‐driver interactions (CO2 and temperature, CO2 and light), based on data of a published meta‐analysis on multiple‐driver laboratory experiments. The effect of this parametrization on phytoplankton biomass and community composition is tested using present‐day and future high‐emission (SSP5‐8.5) climate forcing. While the projected decrease in future total global phytoplankton biomass in simulations with driver interactions is similar to that in control simulations without driver interactions (5%–6%), interactive driver effects are group‐specific. Globally, diatom biomass decreases more with interactive effects compared with the control simulation (−8.1% with interactions vs. no change without interactions). Small‐phytoplankton biomass, by contrast, decreases less with on‐going climate change when the model accounts for driver interactions (−5.0% vs. −9.0%). The response of global coccolithophore biomass to future climate conditions is even reversed when interactions are considered (+33.2% instead of −10.8%). Regionally, the largest difference in the future phytoplankton community composition between the simulations with and without driver interactions is detected in the Southern Ocean, where diatom biomass decreases (−7.5%) instead of increases (+14.5%), raising the share of small phytoplankton and coccolithophores of total phytoplankton biomass. Hence, interactive effects impact the phytoplankton community structure and related biogeochemical fluxes in a future ocean. Our approach is a first step to integrate the mechanistic understanding of interacting driver effects on phytoplankton growth gained by numerous laboratory experiments into a global ocean biogeochemistry model, aiming toward more realistic future projections of phytoplankton biomass and community composition. [ABSTRACT FROM AUTHOR]

Background: Some oral conditions can have psychosocial consequences that affect children's daily life and well‐being. Aim: To create a structural model for the determination of dental caries, molar–incisor hypomineralization (MIH), and the impact of these conditions and socioeconomic status on schoolchildren's oral health‐related quality of life (OHRQoL). Design: A representative cross‐sectional study was conducted in Lavras, Brazil, with 1181 female and male schoolchildren 8–9 years of age. OHRQoL was measured using the Brazilian version of the CPQ8‐10. Clinical examinations were performed by a calibrated dentist for the diagnosis of dental caries (WHO) and MIH (EAPD). Parents/caregivers answered questionnaires addressing the child's medical history and socioeconomic status. Data were analyzed using structural equation modeling. Results: The model revealed that greater MIH severity (β =.874; p <.001) and worse socioeconomic status (β = −.060; p =.001) were associated with a greater number of teeth with caries experience. The higher the number of teeth with caries experience (β =.160; p =.007) and worse socioeconomic status (β = −.164; p <.001), the greater the negative impact on OHRQoL. Conclusion: The model created showed that dental caries and socioeconomic status had a direct negative impact on the OHRQoL of schoolchildren and MIH had an indirect impact mediated by the occurrence of caries experience. [ABSTRACT FROM AUTHOR]

In recent decades, the Arctic Ocean has experienced continuous warming and freshening, affecting biogeochemical factors such as nutrient supply, light availability, chlorophyll, and productivity. While Arctic marine productivity is projected to increase due to the expansion of the open ocean and increased chlorophyll concentration, uncertainties related to chlorophyll and nutrients may distract the fidelity of productivity in current Earth system models (ESMs). Here, we analyze the existing uncertainty in the Arctic chlorophyll projections using the 26 ESMs participating in Coupled Model Intercomparison Projects 5 and 6 (CMIP5 and CMIP6). We found that the uncertainty in the Arctic chlorophyll projections in the CMIP6 ESMs is greater than in the CMIP5 ESMs due to increasing uncertainty in the background nitrate concentration. A significant relationship between background nitrate and projected chlorophyll (r = 0.86) is demonstrated using the observational climatology of nitrate. Based on this strong relationship, the emergent constraint is applied to reduce the uncertainty of future chlorophyll projections. Declines in chlorophyll concentration based on emergent constraint are estimated to be further decreased in the future (44.9% ±29.1 $\pm \,29.1$% to 50.9% ±27.6 $\pm \,27.6$%) than at present, which is about three‐fold larger than the multi‐model mean projection (−13.5% ±48.7 $\pm \,48.7$%). Comparing cumulative density functions before and after the emergent constraint, the probability of the decreasing chance of chlorophyll is increased by approximately 36% from 60% in prior CMIP5,6 to 93%–96% after constraint. Our results imply that reducing the uncertainty in background nitrate concentration can improve the fidelity of future projections of the Arctic ecosystem in the ESMs. Plain Language Summary: The Arctic Ocean environment has undergone changes in response to human‐induced greenhouse gases, such as dramatic warming and sea‐ice retreat. Recently, the chlorophyll concentration, the proxy of the phytoplankton biomass, has increased leading to an increase in marine productivity in the Arctic Ocean. However, there is a large uncertainty in the current earth system models (ESMs) regarding future changes in phytoplankton biomass. In this study, we analyze the 26 ESMs and estimate the future changes in phytoplankton biomass based on the relationship between current climate and future changes, which is known as the "emergent constraint." We find a strong relationship between the level of current nitrate levels and future chlorophyll changes in the Arctic Ocean. Based on this relationship, we estimate the uncertainty of the Arctic chlorophyll decline, which is about three times larger than the multi‐model mean projection. Our results suggest that reducing the uncertainty of present‐climate nitrate in the ESMs is important for projecting Arctic productivity. Key Points: The CMIP6 models exhibit twice the inter‐model diversity in chlorophyll concentration compared to the CMIP5 models in the Arctic OceanThe large uncertainty in the Arctic chlorophyll projections is caused by the magnitude of the simulated summer nitrate climatologyConstrained by the nitrate observations, the future decline in Arctic chlorophyll is estimated to be three times larger than the multi‐model mean [ABSTRACT FROM AUTHOR]

Through daily exposure to the surrounding input structured in conversations, children's language gradually develops into rich linguistic constructions that contain multiple cross‐modal elements subtly used together for rich communicative functions. Children demonstrate their skills to resort to multiple semiotic resources in their daily interactions and expertly use them according to their expressive needs and communicative intents. Usage‐based (Tomasello, 2003) and cognitive linguistics (Langacker, 1988) as well as construction grammar (Goldberg, 2006) have enriched our comprehension of the processes at work. Those approaches need to be combined to gesture studies (Kendon, 1988; McNeill, 1992) and multimodal approaches (Andren, 2010; Morgenstern, 2014) to fully capture the orchestration of the semiotic resources at play (Cienki, 2012; Müller, 2009). But child language development cannot be understood outside its interactional, dialogic context (Bakhtin, 1981) and without taking into account the role of expert languagers (Vygotsky, 1934) in routines or formats (Bruner, 1975). The first section thus extensively focuses on a productive combination of theoretical approaches and methods, which have been essential to understand child language development, but analyzing child language is also necessary in turn to ground socio‐cognitive and interactional approaches to language. The salient features of the variably multimodal child's development are presented in the second section. The third section illustrates longitudinal pathways into multimodal languaging thanks to detailed analyses of adult‐child interactive sequences. This article is categorized under:Cognitive Biology > Cognitive DevelopmentComputer Science and Robotics > Natural Language ProcessingLinguistics > Language AcquisitionLinguistics > Cognitive Linguistics [ABSTRACT FROM AUTHOR]

Summary: Root hairs and soil water content are crucial in controlling the release and diffusion of root exudates and shaping profiles of biochemical properties in the rhizosphere. But whether root hairs can offset the negative impacts of drought on microbial activity remains unknown.Soil zymography, 14C imaging and neutron radiography were combined to identify how root hairs and soil moisture affect rhizosphere biochemical properties. To achieve this, we cultivated two maize genotypes (wild‐type and root‐hair‐defective rth3 mutant) under ambient and drought conditions.Root hairs and optimal soil moisture increased hotspot area, rhizosphere extent and kinetic parameters (Vmax and Km) of β‐glucosidase activities. Drought enlarged the rhizosphere extent of root exudates and water content. Colocalization analysis showed that enzymatic hotspots were more colocalized with root exudate hotspots under optimal moisture, whereas they showed higher dependency on water hotspots when soil water and carbon were scarce.We conclude that root hairs are essential in adapting rhizosphere properties under drought to maintain plant nutrition when a continuous mass flow of water transporting nutrients to the root is interrupted. In the rhizosphere, soil water was more important than root exudates for hydrolytic enzyme activities under water and carbon colimitation. See also the Commentary on this article by Zhang et al., 237: 707–709. [ABSTRACT FROM AUTHOR]

In this study, we hypothesized that shifts in the kinetic parameters of extracellular hydrolytic enzymes may occur as a consequence of seasonal environmental disturbances and would reflect the level of adaptation of the bacterial community to the organic matter of the ecosystem. We measured the activities of enzymes that play a key role in the bacterial growth (leucine aminopeptidase, β‐ and α‐glucosidases) in surface coastal waters of the Eastern Cantabrian Sea and determined their kinetic parameters by computing kinetic models of distinct complexity. Our results revealed the existence of two clearly distinct enzymatic systems operating at different substrate concentrations: a high‐affinity system prevailing at low substrate concentrations and a low‐affinity system characteristic of high substrate concentrations. These findings could be the result of distinct functional bacterial assemblages growing concurrently under sharp gradients of high‐molecular‐weight compounds. We constructed an ecological network based on contemporaneous and time‐delayed correlations to explore the associations between the kinetic parameters and the environmental variables. The analysis revealed that the recurring phytoplankton blooms registered throughout the seasonal cycle trigger the wax and wane of those members of the bacterial community able to synthesize and secrete specific enzymes. [ABSTRACT FROM AUTHOR]

Color appearance models (CAM) generate a set of visual correlates attributed to a stimulus such as hue, brightness, and saturation. However, most of their applicability is limited to stimuli perceived on a uniform background. Additionally, when focusing on brightness, multiple studies have been performed to model the mechanisms of brightness perception of a stimulus on a non‐uniform background. In this paper, experimental data are gathered and the insights of both approaches are combined. The influence of adding a neutral ring‐shaped luminous area in the background of a neutral circular stimulus has been investigated via a series of psychophysics experiments. The ring is presented at three luminance levels (90, 335, 1200 cd/m2) with three thicknesses (0.33, 0.67, and 1.00 cm) at four angular distances to the edge of the stimulus (1.2°, 6.4°, 11.3° and 16.1°). It is observed that when the ring is closer to the stimulus, the brightness inhibition becomes larger; obviously, the impact is also related to the ring's area and luminance. Inspired by the classical CAM, the cone excitations corresponding to the stimulus and the background are inserted in a compression‐adaptation formula to obtain a cone response proportional to the perceived brightness. The semi‐saturation constant occurring in this formula is modelled as a function of the cone excitation, the distance and the width of the ring. The results are overall promising, yet the model shows some shortcomings and more complex weighting functions might be needed. In the future, image‐based approaches should get more attention. [ABSTRACT FROM AUTHOR]

Regional brain iron accumulation is observed in many neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease, and is associated with cognitive decline. We explored associations between age, cognition and iron content in grey matter regions and hippocampal subfields in 380 participants of the Aberdeen children of the 1950s cohort and their first‐generation relatives (aged 26–72 years). Participants underwent cognitive assessment at the time of MRI scanning. Quantitative susceptibility mapping of these MRI data was used to assess iron content in grey matter regions and in hippocampal subfields. Principle component analysis was performed on cognitive test scores to create a general cognition score. Spline analysis was used with the Akaike information criterion to determine if order 1, 2 or 3 natural splines were optimal for assessing non‐linear relationships between regional iron and age. Multivariate linear models were used to assess associations between regional iron and cognition. Higher iron correlated with older age in the left putamen across all ages and in the right putamen of only participants over 58. Whereas a decrease in iron with older age was observed in the right thalamus and left pallidum across all ages. Right amygdala iron levels were associated with poorer general cognition scores and poorer immediate recall scores. Iron was not associated with any measures of cognitive performance in other regions of interest. Our results suggest that, whilst iron in some regions was associated with cognitive performance, there is an overall lack of association between regional iron content and cognitive ability in cognitively healthy individuals. [ABSTRACT FROM AUTHOR]

Accurate estimation of regional and global patterns of ecosystem respiration (ER) is crucial to improve the understanding of terrestrial carbon cycles and the predictive ability of the global carbon budget. However, large uncertainties still exist in regional and global ER estimation due to the drawbacks of modeling methods. Based on eddy covariance ER data from 132 sites in China from 2002 to 2020, we established Intelligent Random Forest (IRF) models that integrated ecological understanding with machine learning techniques to estimate ER. The results showed that the IRF models performed better than semiempirical models and machine learning algorithms. The observed data revealed that gross primary productivity (GPP), living plant biomass, and soil organic carbon (SOC) were of great importance in controlling the spatiotemporal variability of ER across China. An optimal model governed by annual GPP, living plant biomass, SOC, and air temperature (IRF‐04 model) matched 93% of the spatiotemporal variation in site‐level ER, and was adopted to evaluate the spatiotemporal pattern of ER in China. Using the optimal model, we obtained that the annual value of ER in China ranged from 5.05 to 5.84 Pg C yr−1 between 2000 and 2020, with an average value of 5.53 ± 0.22 Pg C yr−1. In this study, we suggest that future models should integrate process‐based and data‐driven approaches for understanding and evaluating regional and global carbon budgets. Plain Language Summary: With China already committing to achieve carbon neutrality before 2060, an accurate assessment of land carbon sink and its flux rate in China is an increasingly important area in global change ecology. In this essay, a high‐efficiency and accurate simulation method was introduced in this field; This method is particularly useful in the assessment of carbon sink and its flux rate in China by combining with reliable observation flux data. Using this new method, a reliable and reasonable value of carbon flux (ecosystem respiration) was obtained. Meanwhile, that method provides a better understanding of the mechanism governing the spatiotemporal variability of carbon flux. Therefore, this present study has gone some way toward enhancing our understanding of a comprehensive assessment and analysis of land carbon sink in China. Key Points: A model integrating ecological knowledge and machine learning was established to estimate ecosystem respiration (ER) in ChinaThe spatiotemporal patterns of ER are significantly affected by productivity, plant biomass, soil organic carbon, and air temperatureChina's ER was estimated to be 5.53 ± 0.22 petagrams of carbon per year (Pg C yr−1) on average for the years 2000–2020 [ABSTRACT FROM AUTHOR]

The modern definition of enzymology is synonymous with the Michaelis–Menten equation instituted by Leonor Michaelis and Maud Menten. Most textbooks, or chapters within, discussing enzymology start with the derivation of the equation under the assumption of rapid equilibrium (as done by Michaelis–Menten) or steady state (as modified by Briggs and Haldane) conditions to highlight the importance of this equation as the bedrock on which interpretation of enzyme kinetic results is dependent. However, few textbooks or monographs take the effort of placing the equation within its right historical context and discuss the assumptions that have gone into its institution. This guide will dwell on these in substantial detail. Further, this guide will attempt to instil a sense of appreciation for the mathematical curve rectangular hyperbola, its unique attributes and how ubiquitous the curve is in biological systems. To conclude, this guide will discuss the limitations of the equation, and the method it embodies, and trace the journey of how investigators are attempting to move beyond the steady‐state approach and the Michaelis–Menten equation into full progress curve, pre–steady state and single‐turnover kinetic analysis to obtain greater insights into enzyme kinetics and catalysis. [ABSTRACT FROM AUTHOR]

Psoriasis is a chronic inflammatory disorder affecting skin and joints that results from immunological dysfunction such as enhanced IL‐23 induced Th‐17 differentiation. IkappaB‐Zeta (IκBζ) is an atypical transcriptional factor of the IκB protein family since, contrary to the other family members, it positively regulates NF‐κB pathway by being exclusively localized into the nucleus. IκBζ deficiency reduces visible manifestations of experimental psoriasis by diminishing expression of psoriasis‐associated genes. It is thus tempting to consider IκBζ as a potential therapeutic target for psoriasis as well as for other IL23/IL17‐mediated inflammatory diseases. In this review, we will discuss the regulation of expression of NFKBIZ and its protein IκBζ, its downstream targets, its involvement in pathogenesis of multiple disorders with emphasis on psoriasis and evidences supporting that inhibition of IκBζ may be a promising alternative to current therapeutic managements of psoriasis. [ABSTRACT FROM AUTHOR]

d‐Glucosaminate‐6‐phosphate ammonia‐lyase (DGL) catalyzes the conversion of d‐glucosaminate‐6‐phosphate to 2‐keto‐3‐deoxyglutarate‐6‐phosphate, with stereospecific protonation of C‐3 of the product. The crystal structure of DGL showed that His‐163 could serve as the proton donor. H163A mutant DGL is fully active in the steady‐state reaction, and the pre‐steady‐state kinetics are very similar to those of wild‐type DGL. However, H163A DGL accumulates a transient intermediate with λmax at 293 nm during the reaction that is not seen with wild‐type DGL. Furthermore, NMR analysis of the reaction of H163A DGL in D2O shows that the product is a mixture of deuterated diastereomers at C‐3. These results establish that His‐163 is the proton donor in the reaction mechanism of DGL. [ABSTRACT FROM AUTHOR]

The structural and electronic properties of epitaxial monolayer graphene on SiC(0001) are examined upon potassium intercalation. Notably, the first real‐space observation via scanning tunneling microscopy of the (2 × 2) superstructure in graphene‐based thin films formed by the potassium atoms below the uppermost graphene layer is presented. Therein, additional signatures stemming from quasiparticle interference effects are found allowing investigations of the electronic bands of K‐intercalated epitaxial monolayer graphene on a local scale. Those data are compared to area‐averaged results obtained from photoelectron spectroscopy. In particular, backfolding of the graphene π bands are found as a consequence of the (2 × 2) superstructure of the K atoms with respect to the graphene lattice. This is accompanied by a strong n‐type doping effect that causes a rigid shift of the Dirac bands to higher binding energies and filling of two parabolic interlayer bands at the Γ point of the surface Brillouin zone of the graphene lattice as well. This electronic configuration is promoted by additional penetration of potassium atoms into the interspace between the SiC substrate and the buffer layer that is located between the substrate and the quasi‐freestanding graphene sheet. Consequently, the epitaxial monolayer graphene sample transforms to n‐doped epitaxial bilayer graphene upon K intercalation. [ABSTRACT FROM AUTHOR]

Noroviruses are major causative agents of nonbacterial acute gastroenteritis in humans. Ten genogroups of noroviruses have been identified to date, among which genogroup I (GI) and genogroup II (GII) noroviruses are major pathogens for humans. GI and GII noroviruses are further classified into nine and 27 genotypes, respectively. Noroviruses are well known to bind to histo‐blood group antigens (HBGAs). Many studies have revealed that virus‐like particles (VLPs) from different genotypes exhibit distinct patterns of HBGA binding, but the assay conditions used in these studies were not identical. To enable comparison of the binding to HBGA of nine GI genotypes, I purified VLPs from insect cells and analysed their HBGA‐binding profiles. Although each genotype exhibited a distinct pattern of HBGA binding, Lewis b antigen was commonly recognized by all of the genogroup I strains, suggesting that this antigen plays a critical role in the pathogenesis of noroviruses. [ABSTRACT FROM AUTHOR]

Summary: Photosynthetic carbon fixation is often limited by CO2 availability, which led to the evolution of CO2 concentrating mechanisms (CCMs). Some diatoms possess CCMs that employ biochemical fixation of bicarbonate, similar to C4 plants, but whether biochemical CCMs are commonly found in diatoms is a subject of debate.In the diatom Phaeodactylum tricornutum, phosphoenolpyruvate carboxylase (PEPC) is present in two isoforms, PEPC1 in the plastids and PEPC2 in the mitochondria. We used real‐time quantitative polymerase chain reaction, Western blots, and enzymatic assays to examine PEPC expression and PEPC activity, under low and high concentrations of dissolved inorganic carbon (DIC).We generated and analyzed individual knockout cell lines of PEPC1 and PEPC2, as well as a PEPC1/2 double‐knockout strain. While we could not detect an altered phenotype in the PEPC1 knockout strains at ambient, low or high DIC concentrations, PEPC2 and the double‐knockout strains grown under ambient air or lower DIC availability conditions showed reduced growth and photosynthetic affinity for DIC while behaving similarly to wild‐type (WT) cells at high DIC concentrations. These mutants furthermore exhibited significantly lower 13C/12C ratios compared to the WT.Our data imply that in P. tricornutum at least parts of the CCM rely on biochemical bicarbonate fixation catalyzed by the mitochondrial PEPC2. [ABSTRACT FROM AUTHOR]

The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain this takes place, remain important scientific challenges. But technological and computational advances in neuroscience and artificial intelligence now provide unprecedented opportunities to study the human brain in action as language is read and understood. Recent contextualized language models seem to be able to capture homonymic meaning variation ("bat", in a baseball vs. a vampire context), as well as more nuanced differences of meaning-for example, polysemous words such as "book", which can be interpreted in distinct but related senses ("explain a book", information, vs. "open a book", object) whose differences are fine-grained. We study these subtle differences in lexical meaning along the concrete/abstract dimension, as they are triggered by verb-noun semantic composition. We analyze functional magnetic resonance imaging (fMRI) activations elicited by Italian verb phrases containing nouns whose interpretation is affected by the verb to different degrees. By using a contextualized language model and human concreteness ratings, we shed light on where in the brain such fine-grained meaning variation takes place and how it is coded. Our results show that phrase concreteness judgments and the contextualized model can predict BOLD activation associated with semantic composition within the language network. Importantly, representations derived from a complex, nonlinear composition process consistently outperform simpler composition approaches. This is compatible with a holistic view of semantic composition in the brain, where semantic representations are modified by the process of composition itself. When looking at individual brain areas, we find that encoding performance is statistically significant, although with differing patterns of results, suggesting differential involvement, in the posterior superior temporal sulcus, inferior frontal gyrus and anterior temporal lobe, and in motor areas previously associated with processing of concreteness/abstractness., (© 2023 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

Summary: To acquire phosphorus, cyanobacteria use the typical bacterial ABC‐type phosphate transporter, which is composed of a periplasmic high‐affinity phosphate‐binding protein PstS and a channel formed by two transmembrane proteins PstC and PstA. A putative pstS gene was identified in the genomes of cyanophages that infect the unicellular marine cyanobacteria Prochlorococcus and Synechococcus. However, it has not been determined whether the cyanophage PstS protein is functional during infection to enhance the phosphate uptake rate of host cells. Here we showed that the cyanophage P‐SSM2 PstS protein was abundant in the infected Prochlorococcus NATL2A cells and the host phosphate uptake rate was enhanced after infection. This is consistent with our biochemical and structural analyses showing that the phage PstS protein is indeed a high‐affinity phosphate‐binding protein. We further modelled the complex structure of phage PstS with host PstCA and revealed three putative interfaces that may facilitate the formation of a chimeric ABC transporter. Our results provide insights into the molecular mechanism by which cyanophages enhance the phosphate uptake rate of cyanobacteria. Phosphate acquisition by infected bacteria can increase the phosphorus contents of released cellular debris and virus particles, which together constitute a significant proportion of the marine dissolved organic phosphorus pool. [ABSTRACT FROM AUTHOR]

Cells rapidly remodel their proteomes to align their cellular metabolism to environmental conditions. Ubiquitin E3 ligases enable this response, by facilitating rapid and reversible changes to protein stability, localization, or interaction partners. In Saccharomyces cerevisiae, the GID E3 ligase regulates the switch from gluconeogenic to glycolytic conditions through induction and incorporation of the substrate receptor subunit Gid4, which promotes the degradation of gluconeogenic enzymes. Here, we show an alternative substrate receptor, Gid10, which is induced in response to changes in temperature, osmolarity, and nutrient availability, regulates the ART‐Rsp5 ubiquitin ligase pathway, a component of plasma membrane quality control. Proteomic studies reveal that the levels of the adaptor protein Art2 are elevated upon GID10 deletion. A crystal structure shows the basis for Gid10‐Art2 interactions, and we demonstrate that Gid10 directs a GID E3 ligase complex to ubiquitinate Art2. Our data suggest that the GID E3 ligase affects Art2‐dependent amino acid transport. This study reveals GID as a system of E3 ligases with metabolic regulatory functions outside of glycolysis and gluconeogenesis, controlled by distinct stress‐specific substrate receptors. SYNOPSIS: The GID E3 ligase utilizes swappable substrate receptors to maintain cellular homeostasis during distinct environmental perturbations. During heat stress, the substrate receptor Gid10 regulates the ART‐Rsp5 ubiquitin ligase pathway, a component of plasma membrane quality control. The substrate receptor Gid10 directs a GID E3 ligase assembly to ubiquitinate the adaptor protein Art2.A crystal structure shows the basis of Art2 binding to Gid10.The GID E3 ligase affects Art2‐dependent amino acid transport, revealing a regulatory role of the GID E3 ligase outside of glycolysis and gluconeogenesis. [ABSTRACT FROM AUTHOR]

Soil enzymes are central to ecosystem processes because they mediate numerous reactions that are essential in biogeochemical cycles. However, how soil enzyme activities will respond to global warming is uncertain. We reviewed the literature on mechanisms linking temperature effects on soil enzymes and microbial communities, and outlined a conceptual overview on how these changes may influence soil carbon fluxes in terrestrial ecosystems.At the enzyme scale, although temperature can have a positive effect on enzymatic catalytic power in the short term (i.e. via the instantaneous response of activity), this effect can be countered over time by enzyme inactivation and reduced substrate affinity. At the microbial scale, short‐term warming can increase enzymatic catalytic power via accelerated synthesis and microbial turnover, but shifts in microbial community composition and growth efficiency may mediate the effect of warming in the long term.Although increasing enzyme activities may accelerate labile carbon decomposition over months to years, our literature review highlights that this initial stage can be followed by the following phases: (a) a reduction in soil carbon loss, due to changing carbon use efficiency among communities or substrate depletion, which together can decrease microbial biomass and enzyme activity and (b) an acceleration of soil carbon loss, due to shifts in microbial community structure and greater allocation to oxidative enzymes for recalcitrant carbon degradation. Studies that bridge scales in time and space are required to assess whether there will be an attenuation or acceleration of soil carbon loss through changes in enzyme activities in the very long term.We conclude that soil enzymes determine the sensitivity of soil carbon to warming, but that the microbial community and enzymatic traits that mediate this effect change over time. Improving representation of enzymes in soil carbon models requires long‐term studies that characterize the response of wide‐ranging hydrolytic and oxidative enzymatic traits—catalytic power, kinetics, inactivation—and the microbial community responses that govern enzyme synthesis. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

We consider two systems of nonlinear first‐order ordinary differential equations proposed to describe Ca2+‐levels in renal vascular smooth muscle cells and in liver cells. Initially, we present the models and its assumptions. We next investigate an approach to local solvability by Picard–Lindelöf 's Theorem. Further, we prove nonnegativity of the systems' possible solutions and we especially conclude global unique existence of the models' solutions by Gronwall‐type arguments and the concept of trapping regions. After finishing our theoretical part with some aspects of stability analysis, we provide evidence of our findings by some numerical experiments. [ABSTRACT FROM AUTHOR]

Spatial synchrony may be tail‐dependent, that is, stronger when populations are abundant than scarce, or vice‐versa. Here, 'tail‐dependent' follows from distributions having a lower tail consisting of relatively low values and an upper tail of relatively high values. We present a general theory of how the distribution and correlation structure of an environmental driver translates into tail‐dependent spatial synchrony through a non‐linear response, and examine empirical evidence for theoretical predictions in giant kelp along the California coastline. In sheltered areas, kelp declines synchronously (lower‐tail dependence) when waves are relatively intense, because waves below a certain height do little damage to kelp. Conversely, in exposed areas, kelp is synchronised primarily by periods of calmness that cause shared recovery (upper‐tail dependence). We find evidence for geographies of tail dependence in synchrony, which helps structure regional population resilience: areas where population declines are asynchronous may be more resilient to disturbance because remnant populations facilitate reestablishment. [ABSTRACT FROM AUTHOR]

What is the effect of activating a single modulatory neuronal receptor type on entire brain network dynamics? Can such effect be isolated at all? These are important questions because characterizing elementary neuronal processes that influence network activity across the given anatomical backbone is fundamental to guide theories of brain function. Here, we introduce the concept of the cortical 'receptome' taking into account the distribution and densities of expression of different modulatory receptor types across the brain's anatomical connectivity matrix. By modelling whole‐brain dynamics in silico, we suggest a bidirectional coupling between modulatory neurotransmission and neuronal connectivity hardware exemplified by the impact of single serotonergic (5‐HT) receptor types on cortical dynamics. As experimental support of this concept, we show how optogenetic tools enable specific activation of a single 5‐HT receptor type across the cortex as well as in vivo measurement of its distinct effects on cortical processing. Altogether, we demonstrate how the structural neuronal connectivity backbone and its modulation by a single neurotransmitter system allow access to a rich repertoire of different brain states that are fundamental for flexible behaviour. We further propose that irregular receptor expression patterns—genetically predisposed or acquired during a lifetime—may predispose for neuropsychiatric disorders like addiction, depression and anxiety along with distinct changes in brain state. Our long‐term vision is that such diseases could be treated through rationally targeted therapeutic interventions of high specificity to eventually recover natural transitions of brain states. [ABSTRACT FROM AUTHOR]

Systemic inflammation is associated with chronic disease and is purported to be a main pathogenic mechanism underlying metabolic conditions. Microbes harbored in the host gastrointestinal tract release signaling byproducts from their cell wall, such as lipopolysaccharides (LPS), which can act locally and, after crossing the gut barrier and entering circulation, also systemically. Defined as metabolic endotoxemia, elevated concentrations of LPS in circulation are associated with metabolic conditions and chronic disease. As such, measurement of LPS is highly prevalent in animal and human research investigating these states. Indeed, LPS can be a potent stimulant of host immunity, but this response depends on the microbial species’ origin, a parameter often overlooked in both preclinical and clinical investigations. Indeed, the lipid A portion of LPS is mutable and comprises the main virulence and endotoxic component, thus contributing to the structural and functional diversity among LPSs from microbial species. In this review, we discuss how such structural differences in LPS can induce differential immunological responses in the host. [ABSTRACT FROM AUTHOR]

Quantitative systems pharmacology (QSP) is a relatively new discipline within modelling and simulation that has gained wide attention over the past few years. The application of QSP models spans drug‐target identification and validation, through all drug development phases as well as clinical applications. Due to their detailed mechanistic nature, QSP models are capable of extrapolating knowledge to predict outcomes in scenarios that have not been tested experimentally, making them an important resource in experimental and clinical pharmacology. However, these models are complicated to work with due to their size and inherent complexity. This makes many applications of QSP models for simulation, parameter estimation and trial design computationally intractable. A number of techniques have been developed to simplify QSP models into smaller models that are more amenable to further analyses while retaining their accurate predictive capabilities. Different simplification techniques have different strengths and weaknesses and hence different utilities. Understanding the utilities of different methods is essential for selection of the best method for a particular situation. In this paper, we have created an overall framework for model simplification techniques that allows a natural categorisation of methods based on their utility. We provide a brief description of the concept underpinning the different methods and example applications. A summary of the utilities of methods is intended to provide a guide to modellers in their model endeavours to simplify these complicated models. [ABSTRACT FROM AUTHOR]

Climate change has lengthened wildfire seasons and transformed fire regimes throughout the world. Thus, capturing fuel and fire dynamics is critical for projecting Earth system processes in warmer and drier future. Recent advances in fire regime modeling have linked land surface models with fire behavior models. Such models often rely on fine surface fuels to drive fire behavior and effects, and while many models can simulate processes that control how these fuels change through time (i.e., fine fuel accumulation), fuel loading estimates remain highly uncertain, largely due to uncertainties in the algorithms controlling decomposition. Uncertainties are often amplified in climate change forecasts when initial conditions and feedbacks are not well represented. The goal of this review is to highlight fine fuel decomposition as a key uncertainty in model systems. We review the current understanding of mechanisms controlling decomposition, describe how they are incorporated into models, and evaluate the uncertainties associated with different approaches. We also use three state‐of‐the‐art land surface fire regime models to demonstrate the sensitivity of decomposition and subsequent wildfire projections to both parameter and model structure uncertainty and show that sensitivity can increase substantially under future climate warming. Given that many of the governing decomposition equations are based on individual case studies from a single location, and because key parameters are often hard coded, critical uncertainties are currently ignored. It is essential to be transparent about these uncertainties as the domain of land surface models is expanded to include the evaluation of future wildfire regimes. Plain Language Summary: Wildfire is a critical force regulating carbon retention globally. This is especially true in coniferous forests, which store more than one‐third of the Earth's terrestrial carbon. Fine, dead materials on the forest floor (i.e., fine surface fuels) play a key role in driving fire spread. Thus, modeling the role of fire in Earth system processes requires reliable estimates of fine surface fuel loading and projections of how it will change over time (i.e., fine fuel accumulation). To accomplish this, we need models that can account for complex interactions among climate and vegetation—including the effects of temperature and precipitation on plant growth, mortality, litterfall, and litter decay—and that link these dynamics with projections of future wildfire. Although many models are designed to simulate these processes, fuel loading estimates remain highly uncertain. In this paper, we review the current understanding of mechanisms controlling fine fuel accumulation, describe how these mechanisms are represented in models, and evaluate the uncertainties associated with different approaches. We conclude with recommendations for future research needed to better model how climate change will influence fuels, wildfire, and carbon retention. Key Points: Developing land surface models for climate‐fire interactions requires estimating and overcoming uncertainty in fuel accumulation processesModels that simulate fuel accumulation differ in how they parameterize and represent fuel decomposition; assumptions are often hard codedSensitivity to parameter and model structure uncertainty increases with climate warming and decreases with increasing precipitation [ABSTRACT FROM AUTHOR]

Macrophages play an important role in the adaptive immune system. Their ability to neutralize cellular targets through Fc receptor‐mediated phagocytosis has relied upon immunotherapy that has become of particular interest for the treatment of cancer and autoimmune diseases. A detailed investigation of phagocytosis is the key to the improvement of the therapeutic efficiency of existing medications and the creation of new ones. A promising method for studying the process is imaging flow cytometry (IFC) that acquires thousands of cell images per second in up to 12 optical channels and allows multiparametric fluorescent and morphological analysis of samples in the flow. However, conventional IFC data analysis approaches are based on a highly subjective manual choice of masks and other processing parameters that can lead to the loss of valuable information embedded in the original image. Here, we show the application of a Faster region‐based convolutional neural network (CNN) for accurate quantitative analysis of phagocytosis using imaging flow cytometry data. Phagocytosis of erythrocytes by peritoneal macrophages was chosen as a model system. CNN performed automatic high‐throughput processing of datasets and demonstrated impressive results in the identification and classification of macrophages and erythrocytes, despite the variety of shapes, sizes, intensities, and textures of cells in images. The developed procedure allows determining the number of phagocytosed cells, disregarding cases with a low probability of correct classification. We believe that CNN‐based approaches will enable powerful in‐depth investigation of a wide range of biological processes and will reveal the intricate nature of heterogeneous objects in images, leading to completely new capabilities in diagnostics and therapy. [ABSTRACT FROM AUTHOR]

Remote sensing of solar‐induced chlorophyll fluorescence (SIF) provides a powerful proxy for gross primary productivity (GPP). It is particularly promising in boreal ecosystems where seasonal downregulation of photosynthesis occurs without significant changes in canopy structure or chlorophyll content. The use of SIF as a proxy for GPP is complicated by inherent non‐linearities due to both physical (illumination effects) and ecophysiological (light use efficiencies) controls at fine spatial (tower/leaf) and temporal (half‐hourly) scales. To study the SIF‐GPP relationship, we investigated the diurnal and seasonal dynamics of continuous tower‐based measurements of SIF, GPP, and common vegetation indices at the Southern Old Black Spruce Site (SOBS) in Saskatchewan, CA over the course of two years. We find that SIF outperforms other vegetation indices as a proxy for GPP at all temporal scales but shows a non‐linear relationship with GPP at a half‐hourly resolution. At small temporal scales, SIF and GPP are predominantly driven by light and non‐linearity between SIF and GPP is due to the light saturation of GPP. Averaged over daily and monthly scales, the relationship between SIF and GPP is linear due to a reduction in the observed PAR range. Seasonal changes in the light responses of SIF and GPP are driven by changes in light use efficiency which co‐vary with changes in temperature, while illumination and canopy structure partially linearize the SIF‐GPP relationship. Additionally, we find that the SIF‐GPP relationship has a seasonal dependency. Our results help clarify the utility of SIF for estimating carbon assimilation in boreal forests. Plain Language Summary: Remote sensing can help us better understand plants' role in the global carbon cycle. In particular, a small light signal emitted by plants during photosynthesis, known as solar‐induced chlorophyll fluorescence (SIF), is a promising remotely sensed proxy for carbon uptake due to its strong relationship with gross primary productivity (GPP, ecosystem carbon assimilated during photosynthesis) when observed by satellite. Recent work at the leaf and tower‐scale has highlighted differences in the relationship between SIF and GPP, thereby raising questions over the utility of SIF for this purpose. We collect tower‐based SIF and GPP measurements from the southern end of the boreal forest to clarify their connection in boreal ecosystems. We find that temporal resolution is critical for understanding the nuances between SIF and GPP and that light and temperature effects complicate their relationship. Additionally, the relationship between SIF and GPP has a seasonal dependency that should be considered when using SIF. Taken together, our results suggest that SIF is a powerful tool for estimating carbon assimilation in boreal forests, but some key considerations need to be addressed for properly interpreting this faint signal. Key Points: Tower‐based solar‐induced chlorophyll fluorescence (SIF) closely tracks gross primary productivity (GPP) over two years in a mixed‐species boreal forestLight saturation of photosynthesis drives non‐linearity between SIF and GPPThe SIF‐GPP relationship is seasonally variant due to dynamics between LUEF and LUEP [ABSTRACT FROM AUTHOR]

The available carbon (C) to phosphorus (P) ratio in the soil is regulated by extracellular hydrolases for C and P acquisition by microbes and plants. However, the stoichiometric relationship between acquiring C and P in paddy rhizosphere and bulk soils remains unclear. The objective was to explore the underlying mechanisms of C and P acquisition stoichiometry in rhizosphere and bulk soils in response to P fertilization and cellulose addition. Amendment with either cellulose or P separately caused a significant increase in the maximal velocity (Vmax) of C acquisition enzymes (β‐1,4‐glucosidase and β‐cellobiohydrolase) but decreased that of P acquisition enzymes (acid and alkaline phosphomonoesterases) in bulk soil. In contrast, lower Vmax values of C and P acquisition enzymes were observed in rhizosphere soil than in bulk soil. The co‐application of cellulose and P increased the Vmax of P acquisition enzymes in rhizosphere soil but decreased that of only alkaline phosphomonoesterase in bulk soil. Results show that P availability and labile‐C content co‐regulated the P/C acquisition ratio, and two inverse linear relationships were observed. Specifically, the P/C acquisition ratio was negatively related to both the dissolved organic C/Olsen‐P ratio and the microbial biomass C/P ratio in rhizosphere soil. However, the P/C acquisition ratio was positively related to both the dissolved organic C/Olsen‐P ratio and the microbial biomass C/P ratio in bulk soil. Overall, microbes mineralized less organic P to acquire P in paddy soil rhizosphere (i.e., containing higher labile‐C) than in bulk soil (i.e., having lower labile‐C contents). [ABSTRACT FROM AUTHOR]