Pathways of soil organic carbon accumulation are related to microbial life history strategies in fertilized agroecosystems.

Although the formation, turnover, and accumulation of soil organic carbon (SOC) are driven by different fertilizer inputs and their subsequent microbial-mediated transformation, the relationship between changes in plant-derived and microbial-derived components and soil microbial life history strategies under different fertilization regimes has not been well explored. In this study, the changes in microbial necromass carbon (MNC), lignin phenols, and glomalin-related soil protein (GRSP), as well as soil microbial life history strategy were determined in a 16-year field experiment in response to different fertilization regimes, including a no-fertilizer control (C), conventional chemical NPK fertilization (NPK), and partial substitutions of the NPK in chemical fertilizers with a low (30 %) or high (60 %) level of straw (0.3S and 0.6S) or cattle manure (0.3M and 0.6M). The results showed that total lignin phenol content and its contribution to SOC were significantly increased by 88.7 % and 74.2 %, respectively, in high-level straw substitution treatment as compared to chemical fertilization. Both high-level straw and cattle manure substitution increased MNC and total GRSP contents, but did not alter their contributions to SOC compared to chemical fertilization. In fertilized treatments, the high-level cattle manure substitution had the lowest and highest bacterial and fungal K/r ratio, respectively. Bacterial K/r ratio was an important factor in predicting bacterial necromass carbon content and there was a significant negative correlation between them. The ratio of ectomycorrhizal to saprotrophic fungi and fungal diversity were important factors for predicting lignin phenol and GRSP contents, respectively. In addition, the SEMs modeling indicated that straw substitution directly affected lignin phenol and MNC accumulation, whereas cattle manure substitution indirectly affected MNC accumulation by affecting microbial life history strategies. In conclusions, agricultural residues inputs support the formation of a multiple carbon pool of SOC compared to chemical fertilization; and microbial life history strategy is an important driver of SOC formation and affects SOC accumulation and stability in agroecosystems.

Expeditious Synthesis of Spiroindoline Derivatives via Tandem C(sp2)-H and C(sp3)-H Bond Functionalization of N-Methyl-N-nitrosoanilines.

Presented herein is a novel synthesis of pharmaceutically privileged spiroindoline derivatives via cascade reactions of N-methyl-N-nitrosoanilines with diazo homophthalimides. A group of mechanistic studies disclosed that the formation of product involves an unusual reaction mode of N-methyl-N-nitrosoaniline featuring an initial C(sp2)-H bond activation/alkylation followed by a C(sp3)-H bond activation/spiroannulation. To our knowledge, this is the first example in which N-methyl-N-nitrosoaniline acts as a C3N1 synthon to accomplish formal [4+1] spiroannulation with the participation of the N-methyl unit rather than the previously reported C2N1 synthon to undergo formal [3+2] annulation without the participation of the N-methyl unit. In general, this newly developed synthetic protocol features simple and readily accessible starting materials, valuable products, unique reaction mechanism, high efficiency and atom-economy, excellent compatibility with diverse functional groups, and ready scalability.

Strengthen interactions among fungal and protistan taxa by increasing root biomass and soil nutrient in the topsoil than in the soil-rock mixing layer.

Soil depth plays a crucial role in shaping the interactions between soil microbes and nutrient availability. However, there is limited understanding of how bacterial, fungal, and protistan communities respond to different soil depths, particularly in the unique geological context and soil properties of karst regions. Organic matter, total nitrogen, and phosphorus, ammonium, nitrate, and plant root biomass, as well as bacterial and fungal abundances, bacterial and protistan diversity were higher in the 0-20 cm soil layer than those in the 20-40 cm and soil-rock mixing layers. In contrast, soil pH was higher in the 20-40 cm and soil-rock mixing layers than that in the 0-20 cm soil layer. The soil exchange of calcium, nitrate, and root biomass were identified as the primary factors regulating microbial assemblages across the depth transect. Moreover, co-occurrence network analysis revealed a greater degree of connectivity between protistan taxa and fungal taxa in the 0-20 cm soil layer than those in the 20-40 cm and soil-rock mixing layers. In contrast, the number of association links between protist-bacteria and bacteria-bacteria was higher in the soil-rock mixing layers compared to the 0-20 cm soil layer. Actinobacteria, Ascomycota, and unclassified protistan taxa were identified as keystones, displaying the highest number of connections with other microbial taxa. Collectively, these results suggested that the increased plant root biomass, coupled with sufficient available nutrient inputs in the upper 0-20 cm soil layer, facilitates strong interactions among fungal and protistan taxa, which play crucial roles in the topsoil. However, as nutrients become less available with increasing depth, competition among bacterial taxa and the predation between bacterial and protistan taxa intensify. Therefore, these findings indicate the interactions among keystone taxa at different soil depths has the potential to generate ecological implications during vegetation restoration in fragile ecosystems.

Lithology and niche habitat have significant effect on arbuscular mycorrhizal fungal abundance and their interspecific interactions.

The chemical properties of bedrock play a crucial role in shaping the communities of soil and root-associated arbuscular mycorrhizal fungi (AMF). We investigate AMF community composition and diversity in bulk soil, rhizosphere soil, and roots in karst and non-karst forests. Chemical properties of bedrock of the calcium oxide (CaO) and ratio of calcium oxide and magnesium oxide (Ca/Mg), soil pH, and exchangeable Ca2+ were higher in karst carbonate rocks compared to non-karst clastic rocks. Conversely, bedrock phosphorus content (P-rock), silicon dioxide (SiO2) content, and tree diversity exhibited an opposing trend. AMF abundance was higher in non-karst clastic rocks than in karst carbonate rocks. Stronger interspecific interactions among AMF taxa occurred in the bulk soil and rhizosphere soil of non-karst clastic rocks compared to karst carbonate rocks. AMF abundance and diversity were higher in rhizosphere soil and roots, attributed to increasing nutrient availability when compared to the bulk soil. A more complex network within AMF taxa was observed in rhizosphere soil and roots compared to bulk soil due to an increase in AMF abundance and diversity in rhizosphere soil and roots. Comparing non-karst clastic rocks, karst carbonate rocks increased soil nitrogen (N) and P levels, which can be attributed to the elevated content of soil Ca2+ and Mg2+ content, facilitated by the high CaO content and Ca/Mg ratio in the bedrock of karst forests. However, the thicker soil layer exhibited higher soil nutrient storage, resulting in greater tree diversity in non-karst forests. These findings suggest that high tree richness may increase root biomass and secretion of root exudates in non-karst regions, thereby enhancing the abundance of AMF and their interspecies interactions. Consequently, the diverse bedrock properties that drive variations in soil properties, nutrients, and plant diversity can impact AMF communities, ultimately promoting plant growth and contributing to vegetation recovery.

The strengthened impact of water availability at interannual and decadal time scales on vegetation GPP.

Water availability (WA) is a key factor influencing the carbon cycle of terrestrial ecosystems under climate warming, but its effects on gross primary production (EWA-GPP ) at multiple time scales are poorly understood. We used ensemble empirical mode decomposition (EEMD) and partial correlation analysis to assess the WA-GPP relationship (RWA-GPP ) at different time scales, and geographically weighted regression (GWR) to analyze their temporal dynamics from 1982 to 2018 with multiple GPP datasets, including near-infrared radiance of vegetation GPP, FLUXCOM GPP, and eddy covariance-light-use efficiency GPP. We found that the 3- and 7-year time scales dominated global WA variability (61.18% and 11.95%), followed by the 17- and 40-year time scales (7.28% and 8.23%). The long-term trend also influenced 10.83% of the regions, mainly in humid areas. We found consistent spatiotemporal patterns of the EWA-GPP and RWA-GPP with different source products: In high-latitude regions, RWA-GPP changed from negative to positive as the time scale increased, while the opposite occurred in mid-low latitudes. Forests had weak RWA-GPP at all time scales, shrublands showed negative RWA-GPP at long time scales, and grassland (GL) showed a positive RWA-GPP at short time scales. Globally, the EWA-GPP , whether positive or negative, enhanced significantly at 3-, 7-, and 17-year time scales. For arid and humid zones, the semi-arid and sub-humid zones experienced a faster increase in the positive EWA-GPP , whereas the humid zones experienced a faster increase in the negative EWA-GPP . At the ecosystem types, the positive EWA-GPP at a 3-year time scale increased faster in GL, deciduous broadleaf forest, and savanna (SA), whereas the negative EWA-GPP at other time scales increased faster in evergreen needleleaf forest, woody savannas, and SA. Our study reveals the complex and dynamic EWA-GPP at multiple time scales, which provides a new perspective for understanding the responses of terrestrial ecosystems to climate change.

Addition of cellulose and hemicellulose degrading microorganisms intensified nitrous oxide emission during composting.

This study aims to clarify the mechanisms underlying effects of inoculating cellulose and hemicellulose-degrading microorganisms on nitrous oxide (N2O) emissions during composting with silkworm excrement and mulberry branches. Inoculation with cellulose and hemicellulose-degrading microorganisms resulted in significant increases of total N2O emission by 10.4 ± 2.0 % (349.1 ± 6.2 mg N kg-1 dw) and 26.7 ± 2.1 % (400.6 ± 6.8 mg N kg-1 dw), respectively, compared to the control (316.3 ± 3.6 mg N kg-1 dw). The stimulation of N2O emission was attributed to the enhanced contribution of ammonia-oxidizing bacteria (AOB) and denitrifying bacteria to N2O production, as evidenced by the increased AOB amoA and denitrifying nirK gene abundances. Moreover, microbial inoculation stimulated N2O reduction to N2 owing to increased abundances of nosZⅠ and nosZⅠⅠ genes. These findings highlight the necessity to develop cost-effective and environmentally friendly strategies to reduce N2O emissions when cellulose and hemicellulose-degrading microorganisms are inoculated during composting.

Elevated Mercury Deposition, Accumulation, and Migration in a Karst Forest.

The karst forest is one of the extremely sensitive and fragile ecosystems in southwest China, where the biogeochemical cycling of mercury (Hg) is largely unknown. In this study, we investigated the litterfall deposition, accumulation, and soil migration of Hg in an evergreen-deciduous broadleaf karst forest using high-resolution sampling and stable isotope techniques. Results show that elevated litterfall Hg concentrations and fluxes in spring are due to the longer lifespan of evergreen tree foliage exposed to atmospheric Hg0. The hillslope has 1-2 times higher litterfall Hg concentration compared to the low-lying land due to the elevated atmospheric Hg levels induced by topographical and physiological factors. The Hg isotopic model suggests that litterfall Hg depositions account for ∼80% of the Hg source contribution in surface soil. The spatial trend of litterfall Hg deposition cannot solely explain the trend of Hg accumulation in the surface soil. Indeed, soil erosion enhances Hg accumulation in soil of low-lying land, with soil Hg concentration up to 5-times greater than the concentration on the hillslope. The high level of soil Hg migration in the karst forest poses significant ecological risks to groundwater and downstream aquatic ecosystems.

Inverse shielding and mutual exclusion for PET-MR hybrid imaging concerning induced positronium hyperfine splits radiations.

Prevalent PET imaging reconstructs 2γ-photon pairs emitted after an annihilation from para-positronium (p-Ps) and rejects 3γ events from ortho-positronium (o-Ps) as noises. The 3γ/2γ decay ratio is ~ 3/7 in human body theoretically but in fact significantly lower due to pick-off process, hence PET imaging quality is well controlled. In a PET-MR hybrid unit, the MR magnetic field alters positronium decay patterns through magnetic quenching: all o-Ps and excited p-Ps states are split into finer quantum states under strong magnetic field, thus transitions between some triplet and singlet finer states (mz = 0) were no longer forbidden, thus some o-Ps converts to p-Ps spontaneously by emitting hyperfine split (HFS) photons, which also drops 3γ/2γ ratio hence helps PET imaging quality. However, inverse magnetic quenching might also occur if any external source of HFS frequencies is nearby, thus many p-Ps convert to o-Ps by absorbing those HFS photons (induced HFS transitions). This will dramatically increase 3γ/2γ ratio and hence degrade PET imaging quality instantaneously. The HFS spectrum lies in a broad range of microwaves, from 0.02 to 200 GHz. To prevent inverse magnetic quenching, it is necessary to block external microwave sources outside the hybrid vault, by adding a thin metal layer at all directions of the vault. This could be achieved by adopting the metallic Faraday Cage, which was originally for MR shielding, with possible amendment if necessary. The frequencies of excitation pulses in MR imaging overlap with HFS spectrum, however, the chance for mutual interference during hybrid imaging is small, hence there seems no need to veto each other during hybrid scans.

Tree species diversity increases soil microbial carbon use efficiency in a subtropical forest.

Plant communities strongly influence soil microbial communities and, in turn, soil carbon (C) cycling. Microbial carbon use efficiency (CUE) is an important parameter for predicting soil C accumulation, yet how plant and soil microbial community traits influence microbial CUE remains poorly understood. Here, we determined how soil microbial CUE is influenced by plant and soil microbial community traits, by studying a natural gradient of plant species diversity in a subtropical forest. Our results showed that microbial CUE increased with increasing tree species diversity, suggesting a correlation between plant community traits and soil C storage. The specific soil properties that explained the greatest variation in microbial CUE were associated with microbial communities (biomass, enzyme activities and the ratio of oligotrophic to copiotrophic taxa); there were weaker correlations with plant-input properties, soil chemistry and soil organic C quality and its mineral protection. Overall, high microbial CUE was associated with soil properties correlated with increased tree species diversity: higher substrate availability (simple SOM chemical structures and weak mineral organic associations) and high microbial growth rates despite increased community dominance by oligotrophic strategists. Our results point to a mechanism by which increased tree species diversity may increase the forest C sink by affecting carbon use with the soil microbial community.

Mechanisms of mitigating nitrous oxide emission during composting by biochar and calcium carbonate addition.

To investigate the mechanisms underlying effects of biochar and calcium carbonate (CaCO3) addition on nitrous oxide (N2O) emissions during composting, this paper conducted a systematic study on mineral nitrogen (N), dissolved organic carbon (C) and N, sources of N2O, and functional genes. Biochar and CaCO3 addition decreased N2O emissions by 26.5-47.8% (9.5-96.9 mg N kg-1 dw) and 13.9-37.4% (12.0-121.0 mg N kg-1 dw) compared to the control (14.3-179.7 mg N kg-1 dw), respectively. The mitigation of N2O emission was caused by decreased contribution of ammonia-oxidizing bacteria (AOB) and fungi to N2O production due to diminished AOB amoA, fungal nirK and P450 gene abundances, or by stimulated N2O reduction to N2 owing to increased abundances of nosZⅠ and nosZⅠⅠ genes under biochar and CaCO3 addition. The findings suggest that the addition of biochar or CaCO3 is effective in mitigating N2O emission during composting.

Condition-Controlled Selective Synthesis of Pyranone-Tethered Indazoles or Carbazoles through the Cascade Reactions of N-Nitrosoanilines with Iodonium Ylides.

Presented herein is a condition-controlled selective synthesis of pyranone-tethered indazoles or carbazole derivatives via the cascade reactions of N-nitrosoanilines with iodonium ylides. Mechanistically, the formation of the former involves an unprecedented cascade process including nitroso group-directed C(sp2)-H bond alkylation of N-nitrosoaniline with iodonium ylide followed by intramolecular C-nucleophilic addition to the nitroso moiety, solvent-assisted cyclohexanedione ring opening, and intramolecular transesterification/annulation. On the contrary, the formation of the latter involves the initial alkylation followed by intramolecular annulation and denitrosation. These developed protocols feature easily controllable selectivity, mild reaction conditions, a clean and sustainable oxidant (air), and valuable products that are structurally diverse. In addition, the utility of the products was showcased by their facile and diverse transformations into synthetically and biologically interesting compounds.

Tectonic evolution of the Nootka fault zone and deformation of the shallow subducted Explorer plate in northern Cascadia as revealed by earthquake distributions and seismic tomography.

At the northern Cascadia subduction zone, the subducting Explorer and Juan de Fuca plates interact across a transform deformation zone, known as the Nootka fault zone (NFZ). This study continues the Seafloor Earthquake Array Japan Canada Cascadia Experiment to a second phase (SeaJade II) consisting of nine months of recording of earthquakes using ocean-bottom and land-based seismometers. In addition to mapping the distribution of seismicity, including an MW 6.4 earthquake and aftershocks along the previously unknown Nootka Sequence Fault, we also conducted seismic tomography, which delineates the geometry of the shallow subducting Explorer plate (ExP). We derived hundreds of high-quality focal mechanism solutions from the SeaJade II data. The mechanisms manifest a complex regional tectonic state, with normal faulting of the ExP west of the NFZ, left-lateral strike-slip behaviour of the NFZ, and reverse faulting within the overriding plate above the subducting Juan de Fuca plate. Using data from the combined SeaJade I and II catalogs, we have performed double-difference hypocentre relocations and found seismicity lineations to the southeast of, and oriented 18° clockwise from, the subducted NFZ, which we interpret to represent less active small faults off the primary faults of the NFZ. These lineations are not optimally oriented for shear failure in the regional stress field, which we inferred from averaged focal mechanism solutions, and may represent paleo-configurations of the NFZ. Further, active faults interpreted from seismicity lineations within the subducted plate, including the Nootka Sequence Fault, may have originated as conjugate faults within the paleo-NFZ.

Mechanisms underlying the responses of microbial carbon and nitrogen use efficiencies to nitrogen addition are mediated by topography in a subtropical forest.

Microbial carbon use efficiency (CUE) and nitrogen use efficiency (NUE) are key parameters determining the fate of C and N in soils. Atmospheric N deposition has been found to heavily impact multiple soil C and N transformations, but we lack understanding of the responses of CUE and NUE to N deposition, and it remains uncertain whether responses may be mediated by topography. Here, a N addition experiment with three treatment levels (0, 50 and 100 kg N ha-1 yr-1) was conducted in the valley and on the slope of a subtropical karst forest. Nitrogen addition increased microbial CUE and NUE at both topographic positions, but the underlying mechanisms differed. In the valley, the increase in CUE was associated with an increase in soil fungal richness:biomass and lower litter C:N, whereas on the slope, the response was linked with a reduced ratio of dissolved soil organic C (DOC) to available phosphorus (AVP) which reduced respiration, and increased root N:P stoichiometry. In the valley, the increase in NUE was explained by stimulated microbial N growth relative to gross N mineralization, which was associated with increased ratios of soil total dissolved N:AVP and fungal richness:biomass. In contrast, on the slope, the increase in NUE was attributed to reduced gross N mineralization, linked to increased DOC:AVP. Overall, our results highlight how topography-driven soil substrate availability and microbial properties can regulate microbial CUE and NUE.

Assessing the Effect of Slope Position on the Community Assemblage of Soil Diazotrophs and Root Arbuscular Mycorrhizal Fungi.

Considering the crucial role of soil diazotrophs and root arbuscular mycorrhizal fungi (AMF) in soil nutrient cycling during ecosystem restoration, diazotroph and AMF communities may be determined by slope position. However, the effect of slope position on diazotroph and AMF abundance, diversity, and community composition of karst ecosystems remains unknown. In this study, soil diazotrophs and root AMF characteristics on varying slope positions were assessed in a karst shrub ecosystem. The results displayed that the abundance of soil diazotrophs and root AMF diversity were significantly affected by slope position. Diazotroph abundance accompanied by soil nutrient and plant richness was higher on the lower slopes than the upper slopes, whereas root AMF diversity displayed the opposite trend. The soil diazotroph and root AMF community composition differed among the upper, middle, and lower slopes. The dominant taxa of soil diazotrophs and root AMF at the order level were Rhizobiales and Glomerales, respectively. Moreover, the diazotroph order of Nostocales and the AMF order of Paraglomerales were richer on the upper slopes than on the lower slopes. The slope position directly affected the plant diversity and soil nutrient distribution, indirectly affecting the diazotroph and AMF communities. Increased available nitrogen on the lower slope caused great diazotroph abundance by stimulating plant growth with sufficient carbohydrates. However, low soil nutrients and plant diversity but high plant root biomass induced more root AMF diversity on the upper slope than on the lower slope. Therefore, this study expands the knowledge of soil diazotroph and root AMF ecological functions along different slope positions during vegetation recovery for the successive stages of grass and shrub in the karst region.

Assessing Regional Ecosystem Conditions Using Geospatial Techniques-A Review.

Ecosystem conditions at the regional level are critical factors for environmental management, public awareness, and land use decision making. Regional ecosystem conditions may be examined from the perspectives of ecosystem health, vulnerability, and security, as well as other conceptual frameworks. Vigor, organization, and resilience (VOR) and pressure-stress-response (PSR) are two commonly adopted conceptual models for indicator selection and organization. The analytical hierarchy process (AHP) is primarily used to determine model weights and indicator combinations. Although there have been many successful efforts in assessing regional ecosystems, they remain affected by a lack of spatially explicit data, weak integration of natural and human dimensions, and uncertain data quality and analyses. In the future, regional ecosystem condition assessments may be advanced by incorporating recent improvements in spatial big data and machine learning to create more operative indicators based on Earth observations and social metrics. The collaboration between ecologists, remote sensing scientists, data analysts, and scientists in other relevant disciplines is critical for the success of future assessments.

Novel methods for reliability study of multi-dimensional non-linear dynamic systems.

This research presents two unique techniques for engineering system reliability analysis of multi-dimensional non-linear dynamic structures. First, the structural reliability technique works best for multi-dimensional structural responses that have been either numerically simulated or measured over a long enough length to produce an ergodic time series. Second, a novel extreme value prediction method that can be used in various engineering applications is proposed. In contrast to those currently used in engineering reliability methodologies, the novel method is easy to use, and even a limited amount of data can still be used to obtain robust system failure estimates. As demonstrated in this work, proposed methods also provide accurate confidence bands for system failure levels in the case of real-life measured structural response. Additionally, traditional reliability approaches that deal with time series do not have the benefit of being able to handle a system's high dimensionality and cross-correlation across several dimensions readily. Container ship that experiences significant deck panel pressures and high roll angles when travelling in bad weather was selected as the example for this study. The main concern for ship transportation is the potential loss of cargo owing to violent movements. Simulating such a situation is difficult since waves and ship motions are non-stationary and complicatedly non-linear. Extreme movements greatly enhance the role of nonlinearities, activating effects of second and higher order. Furthermore, laboratory testing may also be called into doubt due to the scale and the choice of the sea state. Therefore, data collected from actual ships during difficult weather journeys offer a unique perspective on the statistics of ship movements. This work aims to benchmark state-of-the-art methods, making it possible to extract necessary information about the extreme response from available on-board measured time histories. Both suggested methods can be used in combination, making them attractive and ready to use for engineers. Methods proposed in this paper open up possibilities to predict simply yet efficiently system failure probability for non-linear multi-dimensional dynamic structure.

Bedrock outcrops weakly promote rather than inhibit soil carbon sequestration after vegetation restoration.

Vegetation restoration can increase soil carbon (C) content in karst regions characterized by highly exposed carbonate rocks; however, it remains unclear whether and how bedrock outcrops contribute to soil C-accumulation after vegetation restoration. We aimed to investigate the magnitude and mechanisms of bedrock outcrops on soil C-accumulation after vegetation restoration. Here, we selected 362 fixed locations to investigate changes in soil organic carbon (SOC) content and density before and after cropland restoration in a karst catchment with varying bedrock exposure ratios and initial soil C pools prior to restoration. Active vegetation restoration (i.e., cropland converted to forage grass, plantation forest, and a combination of grass and forest) and natural regeneration (cropland abandoned) were compared, with croplands maintained with no change as the control. Compared to croplands maintained with no change, SOC density significantly increased in the four vegetation restoration types. The SOC accumulation rate was higher for natural regeneration (39 g C m-2 yr-1) than for the three active restoration strategies (18-27 g C m-2 yr-1). SOC accumulation decreased with a higher initial pool size of soil C but increased with nitrogen accumulation and soil exchangeable calcium (Ca2+) concentration. Higher bedrock outcrops reduced soil volume but increased SOC content through their indirect effects on the initial pool size of soil C, external nitrogen inputs, and soil Ca2+ concentration. This weakly promoted rather than inhibited SOC sequestration. Our findings highlight the effectiveness of various restoration strategies in promoting SOC accumulation in karst areas, as well as the need to take bedrock outcrops and initial soil C pools into consideration when modeling SOC dynamics and maximizing C sinks for vegetation restoration.

DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants.

Genomic prediction is an effective way to accelerate the rate of agronomic trait improvement in plants. Traditional methods typically use linear regression models with clear assumptions; such methods are unable to capture the complex relationships between genotypes and phenotypes. Non-linear models (e.g., deep neural networks) have been proposed as a superior alternative to linear models because they can capture complex non-additive effects. Here we introduce a deep learning (DL) method, deep neural network genomic prediction (DNNGP), for integration of multi-omics data in plants. We trained DNNGP on four datasets and compared its performance with methods built with five classic models: genomic best linear unbiased prediction (GBLUP); two methods based on a machine learning (ML) framework, light gradient boosting machine (LightGBM) and support vector regression (SVR); and two methods based on a DL framework, deep learning genomic selection (DeepGS) and deep learning genome-wide association study (DLGWAS). DNNGP is novel in five ways. First, it can be applied to a variety of omics data to predict phenotypes. Second, the multilayered hierarchical structure of DNNGP dynamically learns features from raw data, avoiding overfitting and improving the convergence rate using a batch normalization layer and early stopping and rectified linear activation (rectified linear unit) functions. Third, when small datasets were used, DNNGP produced results that are competitive with results from the other five methods, showing greater prediction accuracy than the other methods when large-scale breeding data were used. Fourth, the computation time required by DNNGP was comparable with that of commonly used methods, up to 10 times faster than DeepGS. Fifth, hyperparameters can easily be batch tuned on a local machine. Compared with GBLUP, LightGBM, SVR, DeepGS and DLGWAS, DNNGP is superior to these existing widely used genomic selection (GS) methods. Moreover, DNNGP can generate robust assessments from diverse datasets, including omics data, and quickly incorporate complex and large datasets into usable models, making it a promising and practical approach for straightforward integration into existing GS platforms.

Case report: Conversion therapy to permit resection of initially unresectable hepatocellular carcinoma.

Most patients with hepatocellular carcinoma (HCC) are diagnosed when the disease is already at an advanced stage, so they are not eligible for resection and their prognosis is poor. The combination of transarterial chemoembolization (TACE) with immune checkpoint inhibitors or tyrosine kinase inhibitors can improve unresectable HCC to the point that patients can be treated with surgery. Here we describe two cases of such "conversion therapy". One patient was a 52-year-old man in Child-Pugh class A with treatment-naive HCC whose 11.3-cm tumor had invaded the middle hepatic vein and right branch of the portal vein. He was treated with TACE plus camrelizumab, and radical resection was performed 3 months later. No evidence of recurrence was observed during 5-month follow-up. The other patient was a 42-year-old man in Child-Pugh class A with HCC involving a 11.4-cm tumor and severe liver cirrhosis. The patient was treated with TACE and lenvatinib, but the embolic effect after one month was unsatisfactory, so the regional treatment was changed to hepatic artery infusion chemotherapy and transcatheter arterial embolization. Radical resection was performed 2 months later, and no recurrence was evident at 1-month follow-up. These cases demonstrate two conversion therapies that may allow patients with initially unresectable HCC to benefit from resection.

Source Diversity of Intermediate Volatility n-Alkanes Revealed by Compound-Specific δ13C-δD Isotopes.

Intermediate volatility organic compounds (IVOCs) are important precursors of secondary organic aerosols, and their sources remain poorly defined. N-alkanes represent a considerable portion of IVOCs in atmosphere, which can be well identified and quantified out of the complex IVOC pool. To investigate the potential source diversity of intermediate volatility n-alkanes (IVnAs, nC12-nC20), we apportioned the sources of IVnAs in the atmosphere of four North China cities, based on their compound-specific δ13C-δD isotope compositions and Bayesian model analysis. The concentration level of IVnAs reached 1195 ± 594 ng/m3. The δ13C values of IVnAs ranged -32.3 to -27.6‰ and δD values -161 to -90‰. The δD values showed a general increasing trend toward higher carbon number alkanes, albeit a zigzag odd-even prevalence. Bayesian MixSIAR model using δ13C and δD compositions revealed that the source patterns of individual IVnAs were inconsistent; the relative contributions of liquid fossil combustion were higher for lighter IVnAs (e.g., nC12-nC13), while those of coal combustion were higher for heavier IVnAs (e.g., nC17-nC20). This result agrees with principal component analysis of the dual isotope data. Overall, coal combustion, liquid fossil fuel combustion, and biomass burning contributed about 47.8 ± 0.1, 35.7 ± 4.0, and 16.3 ± 4.2% to the total IVnAs, respectively, highlighting the importance of coal combustion as an IVnA source in North China. Our study demonstrates that the dual-isotope approach is a powerful tool for source apportionment of atmospheric IVOCs.