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Soil microbes play a crucial role in the carbon (C) cycle; however, they have been overlooked in predicting the terrestrial C cycle. We applied a microbial-explicit Earth system model - the Community Land Model-Microbe (CLM-Microbe) - to investigate the dynamics of soil microbes during 1901 to 2016. The CLM-Microbe model was able to reproduce the variations of gross (GPP) and net (NPP) primary productivity, heterotrophic (HR) and soil (SR) respiration, microbial (MBC) biomass C in fungi (FBC) and bacteria (BBC) in the top 30 cm and 1 m, and dissolved (DOC) and soil organic C (SOC) in the top 30 cm and 1 m during 1901-2016. During the study period, simulated C variables increased by approximately 12 PgC yr-1 for HR, 25 PgC yr-1 for SR, 1.0 PgC for FBC and 0.4 PgC for BBC in 0-30 cm, and 1.2 PgC for FBC and 0.7 PgC for BBC in 0-1 m. Increases in microbial C fluxes and pools were widely found, particularly at high latitudes and in equatorial regions, but we also observed their decreases in some grids. Overall, the area-weighted averages of HR, SR, FBC, and BBC in the top 1 m were significantly correlated with those of soil moisture and soil temperature in the top 1 m. These results suggested that microbial C fluxes and pools were jointly governed by vegetation C input and soil temperature and moisture. Our simulations revealed the spatial and temporal patterns of microbial C fluxes and pools in response to environmental change, laying the foundation for an improved understanding of soil microbial roles in the global terrestrial C cycle.

The positive Arctic–methane (CH 4 ) feedback forms when more CH 4 is released from the Arctic tundra to warm the climate, further stimulating the Arctic to emit CH 4 . This study utilized the CLM-Microbe model to project CH 4 emissions across five distinct Arctic tundra ecosystems on the Alaska North Slope, considering three Shared Socioeconomic Pathway (SSP) scenarios using climate data from three climate models from 2016 to 2100. Employing a hyper-resolution of 5 m × 5 m within 40,000 m 2 domains accounted for the Arctic tundra’s high spatial heterogeneity; three sites were near Utqiaġvik (US-Beo, US-Bes, and US-Brw), with one each in Atqasuk (US-Atq) and Ivotuk (US-Ivo). Simulated CH 4 emissions substantially increased by a factor of 5.3 to 7.5 under the SSP5–8.5 scenario compared to the SSP1–2.6 and SSP2–4.5 scenarios. The projected CH 4 emissions exhibited a stronger response to rising temperature under the SSP5–8.5 scenario than under the SSP1–2.6 and SSP2–4.5 scenarios, primarily due to strong temperature dependence and the enhanced precipitation-induced expansion of anoxic conditions that promoted methanogenesis. The CH 4 transport via ebullition and plant-mediated transport is projected to increase under all three SSP scenarios, and ebullition dominated CH 4 transport by 2100 across five sites. Projected CH 4 emissions varied in temperature sensitivity, with a Q 10 range of 2.7 to 60.9 under SSP1–2.6, 3.8 to 17.6 under SSP2–4.5, and 5.7 to 17.2 under SSP5–8.5. Compared with the other three sites, US-Atq and US-Ivo were estimated to have greater increases in CH 4 emissions due to warmer temperatures and higher precipitation. The fact that warmer sites and warmer climate scenarios had higher CH 4 emissions suggests an intensified positive Arctic–CH 4 feedback in the 21st century. Microbial physiology and substrate availability dominated the enhanced CH 4 production. The simulated intensified positive feedback underscores the urgent need for a more mechanistic understanding of CH 4 dynamics and the development of strategies to mitigate CH 4 across the Arctic.

Explicitly representing microbial processes has been recognized as a key improvement to Earth system models for the realistic projections of soil carbon (C) and climate dynamics. The CLM-Microbe model builds upon the CLM4.5 and explicitly represents two major soil microbial groups, fungi and bacteria. Based on the compiled time-series data of fungal (FBC) and bacterial (BBC) biomass C from nine biomes, we parameterized and validated the CLM-Microbe model, and further conducted sensitivity and uncertainty analysis for simulating C cycling. The model performance was evaluated with mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) for relative change in FBC and BBC. The CLM-Microbe model is able to reasonably capture the seasonal dynamics of FBC and BBC across biomes, particularly for tropical/subtropical forest, temperate broadleaf forest, and grassland, with MAE

Bacteria and fungi, representing two major soil microorganism groups, play an important role in global nutrient biogeochemistry. Biogeographic patterns of bacterial and fungal biomass are of fundamental importance for mechanistically understanding nutrient cycling. We synthesized 1323 data points of phospholipid fatty acid-derived fungal biomass C (FBC), bacterial biomass C (BBC), and fungi:bacteria (F:B) ratio in topsoil, spanning 11 major biomes. The FBC, BBC, and F:B ratio display clear biogeographic patterns along latitude and environmental gradients including mean annual temperature, mean annual precipitation, net primary productivity, root C density, soil temperature, soil moisture, and edaphic factors. At the biome level, tundra has the highest FBC and BBC densities at 3684 (95% confidence interval: 1678–8084) mg kg−1 and 428 (237–774) mg kg−1, respectively; desert has the lowest FBC and BBC densities at 16.92 (14.4–19.89) mg kg−1 and 6.83 (6.1–7.65) mg kg−1, respectively. The F:B ratio varies dramatically, ranging from 1.8 (1.6–2.1) in savanna to 8.6 (6.7–11.0) in tundra. An empirical model was developed for the F:B ratio and it is combined with a global dataset of soil microbial biomass C to produce global maps for FBC and BBC in 0–30 cm topsoil. Across the globe, the highest FBC is found in boreal forest and tundra while the highest BBC is in boreal forest and tropical/subtropical forest, the lowest FBC and BBC are in shrub and desert. Global stocks of living microbial biomass C were estimated to be 12.6 (6.6–16.4) Pg C for FBC and 4.3 (0.5–10.3) Pg C for BBC in topsoil. These findings advance our understanding of the global distribution of fungal and bacterial biomass, which facilitates the incorporation of fungi and bacteria into Earth system models. The global maps of bacterial and fungal biomass serve as a benchmark for validating microbial models in simulating the global C cycle under a changing climate.

Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2 + H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH4 fluxes. The model underestimated the EC-measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape.

Anaplastic lymphoma kinase (ALK) is one of the common oncogenic driver genes in non-small cell lung cancer (NSCLC). Tyrosine kinase inhibitors (TKIs) have achieved excellent therapeutic effects in patients with ALK fusion positive NSCLC. However, patients will eventually develop resistance to TKIs. Acquired molecular drug resistance mechanisms, such as ALK kinase domain mutation, ALK gene amplification and abnormal activation of bypass, are important drug resistance mechanisms affecting the effect of targeted therapy for ALK+ NSCLC. Acquired ALK kinase domain resistance mutations have become the focus of attention. With the deepening and popularization of next-generation sequencing (NGS), the drug resistance mutation spectrum of ALK TKI is becoming clearer, and acquired drug resistance may change dynamically. First, after the treatment failure of the first (G1)/second generation (G2) TKI, the secondary ALK kinase domain resistance mutation is mainly a single point mutation. About 20% of patients develop drug resistance mutations after failure of treatment with crizotinib, mainly L1196M, G1269A, C1156Y and F1174L. The incidence of point mutations following drug resistance to second-generation TKIs (including alectinib, ceritinib, brigatinib and ensartinib) is as high as 50%, and the types are more abundant, such as G1202R/del, F1174C/V and I1171T/N/S. In preclinical trials, compared with crizotinib, the G2 TKI has a higher inhibitory effect on ALK kinase and can cover most ALK resistance mutations, except G1202R/del. In addition to G1202R, F1174C/L and I1171N/S/T are the main drug-resistant mutations of ceritinib and alectinib respectively, and G1269A and E1210K are the main drug-resistant mutations of ensartinib. Secondly, the proportion of ALK double mutation and "off target" increase significantly following the resistance to the G2 TKIs. Following resistance to third generation (G3) TKI lorlatinib, almost all of them are compound mutations, and the degree of resistance is higher. I1171N double mutation and G1202R double mutation spectrum have been found. Among them, G1202R+L1196M double mutation shows high resistance to all ALK TKIs. In addition, after the progress of sequential multi-generation ALK TKI treatment, the original drug resistance sites change, the ratio of wild-type is increased, and the drug resistance mechanism may be more complex. At present, sequential G2/G3 TKIs can inhibit most drug-resistant mutations after crizotinib resistance. After the treatment progress of G2 TKI, the tumor inhibition effect can be achieved by sequential use of other G2 TKI or lorlatinib. For stubbern solvent frontier region mutation, lorlatinib has a significant inhibitory effect on G1202R mutation, while the lorlatinib resistant L1198F mutation and L1198F double mutation can be resensitized to crizotinib. Some compound mutations are sensitive to G2 TKIs, such as I1171N+L1196M and I1171N+G1269A mutations. Most compound drug-resistant mutations have not found effective inhibitors. The new generation TPX-0131 and NVL-655 show excellent antitumor effect in preclinical experiments, especially can overcome ALK compound drug resistance mutation, however, they still need to be verified by clinical trials. Identifying the kinase domain resistance mutation spectrum of ALK TKI and selecting sensitive and efficient TKIs treatment are the research hotspots in recent years. This paper focused on the mechanism of acquired ALK kinase domain resistance, and systematically summarized the relationship between ALK gene background and kinase domain resistance, ALK TKI kinase domain resistance mutation spectrum and treatment strategies. At the same time, repeated biopsy after tumor progression is very important for identifying ALK kinase domain mutations and selecting the most effective treatment strategy.

The life strategies of bacterial communities determine their structure and function and are an important driver of biogeochemical cycling. However, the variations in these strategies under different soil resource conditions remain largely unknown. We explored the bacterial life strategies and changes in structure and functions between Antarctic soils and forest (temperate, subtropical, and tropical) soils. The results showed that the weighted mean rRNA operon copy number in temperate soils was 19.5% lower than that in Antarctic soils, whereas no significant differences were observed among Antarctic, subtropical, and tropical soils. An unexpected result was that bacterial communities in Antarctic soils tended to be copiotrophs, such as Actinobacteriota and Bacteroidota, whereas those in temperate soils tended to be oligotrophs, such as Acidobacteriota and Chloroflexi. Functional predictions showed that in comparison to copiotrophs in Antarctic soils, temperate-inhabiting oligotrophic bacteria exhibited an 84.2–91.1% lower abundance of labile C decomposition genes (hemicellulose, cellulose, monosaccharides, and disaccharides), whereas a 74.4% higher abundance of stable C decomposition (lignin). Genes involved in N cycling (nitrogen fixation, assimilatory nitrate reduction, and denitrification) were 24.3–64.4% lower in temperate soils than in Antarctic soils. Collectively, our study provides a framework for describing the life strategies of soil bacteria, which are crucial to global biogeochemical cycles. [ABSTRACT FROM AUTHOR]

Two categories of GFRP specimens, in nominal diameters of 11.2 mm and 15.6 mm respectively, made of E-glass fibers and a vinylester resin were immersed in alkaline solution, saline solution and tap water solution at room temperature. The mechanical and durability properties of tested GFRP bar specimens were determined through direct tensile test and short-beam shear test after exposure to aggressive solutions for different days. The obtained results indicated that for all tested GFRP bar specimens the failure modes of fiber rupture in the tensile test and horizontal cracking in the short-beam shear test would not obviously change with the increasing of exposure period. However, the impact of immersion solutions on the durability degradation of mechanical properties of GFRP bars appeared in the ultimate strength and displacement at failure, and at room temperature the alkaline solution had a greater impact than another two solutions. Under the same exposure conditions, the resistance to the strength degradation of the GFRP bars with a larger diameter was better than that of the smaller GFRP bars. The comparison results indicated that the strength degradation trend of conditioned GFRP bars presented in our study was basically in agreement with the data given in previous studies.