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The sign and magnitude of permafrost carbon (C)-climate feedback are highly uncertain due to the limited understanding of the decomposability of thawing permafrost and relevant mechanistic controls over C release. Here, by combining aerobic incubation with biomarker analysis and a three-pool model, we reveal that C quality (represented by a higher amount of fast cycling C but a lower amount of recalcitrant C compounds) and normalized CO 2 –C release in permafrost deposits were similar or even higher than those in the active layer, demonstrating a high vulnerability of C in Tibetan upland permafrost. We also illustrate that C quality exerts the most control over CO 2 –C release from the active layer, whereas soil microbial abundance is more directly associated with CO 2 –C release after permafrost thaw. Taken together, our findings highlight the importance of incorporating microbial properties into Earth System Models when predicting permafrost C dynamics under a changing environment. Permafrost stores large quantities of carbon (C), but uncertainty surrounds decomposability differences between active and permafrost layers. Here, Chen et al . use incubation experiments and a 3-pool model to find permafrost layers are equally or more labile, contributing to C vulnerability in Tibetan permafrost.

Global soil organic carbon (SOC) stocks may decline with a warmer climate. However, model projections of changes in SOC due to climate warming depend on microbially-driven processes that are usually parameterized based on laboratory incubations. To assess how lab-scale incubation datasets inform model projections over decades, we optimized five microbially-relevant parameters in the Microbial-ENzyme Decomposition (MEND) model using 16 short-term glucose (6-day), 16 short-term cellulose (30-day) and 16 long-term cellulose (729-day) incubation datasets with soils from forests and grasslands across contrasting soil types. Our analysis identified consistently higher parameter estimates given the short-term versus long-term datasets. Implementing the short-term and long-term parameters, respectively, resulted in SOC loss (–8.2 ± 5.1% or –3.9 ± 2.8%), and minor SOC gain (1.8 ± 1.0%) in response to 5 °C warming, while only the latter is consistent with a meta-analysis of 149 field warming observations (1.6 ± 4.0%). Comparing multiple subsets of cellulose incubations (i.e., 6, 30, 90, 180, 360, 480 and 729-day) revealed comparable projections to the observed long-term SOC changes under warming only on 480- and 729-day. Integrating multi-year datasets of soil incubations (e.g., > 1.5 years) with microbial models can thus achieve more reasonable parameterization of key microbial processes and subsequently boost the accuracy and confidence of long-term SOC projections. As the climate warms, soil carbon stores will likely be degraded by microbes and released as CO 2 , but these predictions are based on laboratory incubations that might not reflect real rates. Here the authors optimize model projections using dozens of short- and long-term incubations in forest and grasslands.

Anthropogenic disturbances have led to substantial declines in grassland legumes worldwide, with consequences for plant nutritional quality, biodiversity, food-web complexity, and ecosystem sustainability. Despite the growing acknowledgment of the significance of legume presence, it has rarely been investigated how the introduction of legumes affects the growth of neighboring plants over time and the underlying mechanisms that influence biomass production during grassland utilization. To address these gaps, we established legume-restored grasslands followed by 7 years of mowing (once a year) and phosphorus (P) application to simulate defoliation management and improve legume performance. We observed significant higher compensatory growth rate and aboveground biomass in legume-restored grasslands compared to naturally restored grasslands. These improvements can be attributed to the combined effect of an increase in legume proportion in plant communities and the improved performance of neighboring plant species after legume restoration (nursing effect). This nursing effect further increased the relative importance of the mass ratio effect in explaining the improved biomass in legume-restored grasslands after mowing. Moreover, the compensatory growth rate in naturally restored grasslands decreased significantly over time, while the compensatory growth rate in legume-restored grasslands tended to increase, indicating higher sustainable biomass production in legume-restored grasslands. P application increased aboveground biomass, but did not alter plant community structure, regardless of whether legumes were used to restore grasslands. Here, we show for the first time that legume introduction can sustainably provide higher biomass production through enhancing compensatory growth in natural grasslands that have suffered from prolonged or intense defoliation. This highlights the critical role of leguminous species in a long-term grassland restoration.

Increases in carbon (C) inputs to soil can replenish soil organic C (SOC) through various mechanisms. However, recent studies have suggested that the increased C input can also stimulate the decomposition of old SOC via priming. Whether the loss of old SOC by priming can override C replenishment has not been rigorously examined. Here we show, through data–model synthesis, that the magnitude of replenishment is greater than that of priming, resulting in a net increase in SOC by a mean of 32% of the added new C. The magnitude of the net increase in SOC is positively correlated with the nitrogen-to-C ratio of the added substrates. Additionally, model evaluation indicates that a two-pool interactive model is a parsimonious model to represent the SOC decomposition with priming and replenishment. Our findings suggest that increasing C input to soils likely promote SOC accumulation despite the enhanced decomposition of old C via priming. The magnitudes of replenishment and priming, two important but opposing fluxes in soil organic carbon (SOC) dynamics, have not been compared. Here the authors show that the magnitude of replenishment is greater than that of priming, resulting in a net SOC accumulation after additional carbon input to soils.

Alzheimer’s disease (AD) emerges as a perturbing neurodegenerative malady, with a profound comprehension of its underlying pathogenic mechanisms continuing to evade our intellectual grasp. Within the intricate tapestry of human health and affliction, the enteric microbial consortium, ensconced within the milieu of the human gastrointestinal tract, assumes a role of cardinal significance. Recent epochs have borne witness to investigations that posit marked divergences in the composition of the gut microbiota between individuals grappling with AD and those favored by robust health. The composite vicissitudes in the configuration of the enteric microbial assembly are posited to choreograph a participatory role in the inception and progression of AD, facilitated by the intricate conduit acknowledged as the gut-brain axis. Notwithstanding, the precise nature of this interlaced relationship remains enshrouded within the recesses of obscurity, poised for an exhaustive revelation. This review embarks upon the endeavor to focalize meticulously upon the mechanistic sway exerted by the enteric microbiota upon AD, plunging profoundly into the execution of interventions that govern the milieu of enteric microorganisms. In doing so, it bestows relevance upon the therapeutic stratagems that form the bedrock of AD’s management, all whilst casting a prospective gaze into the horizon of medical advancements.

Radiotherapy resistance in nasopharyngeal carcinoma (NPC) is a major cause of recurrence and metastasis. Identifying radiotherapy-related biomarkers is crucial for improving patient survival outcomes. This study developed the nasopharyngeal carcinoma radiotherapy sensitivity score (NPC-RSS) to predict radiotherapy response. By evaluating 113 machine learning algorithm combinations, the glmBoost+NaiveBayes model was selected to construct the NPC-RSS based on 18 key genes, which demonstrated good predictive performance in both public and in-house datasets. The study found that NPC-RSS is closely associated with immune features, including chemokine factors and their receptor families and the major histocompatibility complex (MHC). Gene functional analysis revealed that NPC-RSS influences key signaling pathways such as Wnt/β-catenin, JAK-STAT, NF-κB, and T cell receptors. Cell line validation confirmed that SMARCA2 and CD9 gene expression is consistent with NPC-RSS. Single-cell analysis revealed that the radiotherapy-sensitive group exhibited richer immune infiltration and activation states. NPC-RSS can serve as a predictive tool for radiotherapy sensitivity in NPC, offering new insights for precise screening of patients who may benefit from radiotherapy.

Past global change studies have identified changes in species diversity as a major mechanism regulating temporal stability of production, measured as the ratio of the mean to the standard deviation of community biomass. However, the dominant plant functional group can also strongly determine the temporal stability. Here, in a grassland ecosystem subject to 15 years of experimental warming and hay harvest, we reveal that warming increases while hay harvest decreases temporal stability. This corresponds with the biomass of the dominant C 4 functional group being higher under warming and lower under hay harvest. As a secondary mechanism, biodiversity also explains part of the variation in temporal stability of production. Structural equation modelling further shows that warming and hay harvest regulate temporal stability through influencing both temporal mean and variation of production. Our findings demonstrate the joint roles that dominant plant functional group and biodiversity play in regulating the temporal stability of an ecosystem under global change. Species diversity is thought to play an important role in maintaining production stability. Shi et al. demonstrate that the dominant C4 plant also makes a substantial contribution to temporal stability in a grassland ecosystem subject to 15 years of experimental warming and hay harvest.

Lactate, long regarded as a mere by-product of glycolysis, is increasingly recognized as a signaling metabolite and epigenetic regulator through protein lactylation. This lysine-specific post-translational modification functionally couples cellular metabolic states to gene regulatory programs and orchestrates cell type–specific functions across neurons, astrocytes, and microglia, thereby shaping synaptic plasticity, neuroinflammatory responses, and protein aggregation. Accumulating evidence implicates dysregulated lactylation in the pathogenesis of Alzheimer’s disease (AD), where it modulates amyloid-β deposition, tau aggregation, and glial reactivity. In this Review, we summarize the enzymatic regulation of protein lactylation, delineate its context-dependent roles in distinct central nervous system cell types, and highlight its function as a metabolic–epigenetic–immune nexus in AD progression. We further discuss emerging therapeutic strategies targeting lactate metabolism and lactylation pathways, and outline critical knowledge gaps that must be addressed to translate these insights into innovative diagnostic and therapeutic approaches. By integrating metabolic reprogramming, epigenetic control, and cell-specific mechanisms, this Review positions lactylation as a compelling and emerging frontier in AD research.

Alzheimer’s disease (AD), a pressing global public health challenge, is underpinned by multifaceted pathogenic mechanisms. While traditional research has centered on amyloid-β deposition and tau hyperphosphorylation, emerging evidence reveals that metabolic perturbations play a pivotal role in the earliest phases of AD. As the principal regulators of energy homeostasis within the central nervous system, astrocytes orchestrate a multistep metabolic cascade—encompassing glucose uptake, glycolysis, mitochondrial oxidative metabolism, and the release of metabolic intermediates—to sustain neuronal energy supply and synaptic integrity. In the AD milieu, this astrocytic metabolic cascade becomes profoundly disrupted at every level. Such metabolic dysregulation not only compromises the neuroprotective functions of astrocytes but also directly accelerates synaptic degeneration, exacerbates Aβ and tau pathologies, and amplifies neuroinflammatory responses, collectively forming a core “metabolic-neurodegeneration” pathological axis. Here, we provide a comprehensive synthesis of the aberrant astrocytic metabolic cascade in AD, delineating its critical contributions to synaptic deterioration, proteinopathy progression, and inflammatory escalation. Building on these insights, we propose a conceptual model of an “astrocyte-centric metabolic collapse,” highlighting metabolic derailment as a fundamental initiating and amplifying force in AD pathogenesis. Furthermore, we evaluate therapeutic strategies targeting key nodes of this cascade and discuss the challenges and opportunities inherent in modulating astrocytic metabolism. Through integrating the most recent advances, this review offers a refined understanding of astrocytic metabolic dysregulation in AD and examines its potential as a promising avenue for therapeutic intervention.

Long‐term, slow ecological processes such as changes in plant community structure and composition strongly regulate ecosystem responses to climate change. Shifts in plant community are expected in chronically altered environments under warming. However, experimental evidence for long‐term shifts and the associated mechanisms is still scarce in temperate grasslands. Here, we explore the long‐term responses of a prairie plant community to 14‐year (2000–2013) manipulations of climate warming and clipping in Oklahoma, USA. Infrared heaters were used to elevate soil temperature by about 2 °C all year round, and annual clipping was applied to mimic hay harvest. Community composition was resistant to experimental warming in the first seven years, but started to show responses starting from the eighth year; clipping consistently affected community composition over the years. Compositional change under long‐term warming was mainly due to one invasive species and three dominant species. The negative correlations in relative abundance between the invasive species and the dominant species suggest interspecific competition. Community structure (i.e. richness, evenness and diversity) had no overall response to experimental warming. However, in 2007, the extreme wet year, warming reduced species richness by 30%. Clipping promoted species richness by 10% on average over the 14 years but decreased community evenness. Warming did not interact with clipping in influencing the plant community variables. Synthesis. Our study provides experimental evidence for long‐term shifts in plant community composition due to warming and revealed novel mechanisms (i.e. species invasion and associated biotic interactions) underlying the long‐term shift. The results also suggest that climate extremes may elicit or advance community responses to climate warming. The findings highlight that long‐term climate change experiments are essential to reveal potential shifts in community composition.