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Global and regional soil organic carbon estimates: Magnitudes and uncertainties

Pedosphere 2024年第04期34卷 685-698页

作者： Ziqi LIN Yongjiu DAI Umakant MISHRA Guocheng WANG Wei SHANGGUAN Wen ZHANG Zhangcai QIN School of Atmospheric Sciences Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Sun Yat-sen University Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) computational biology & Biophysics Sandia National Laboratories Faculty of Geographical Science Beijing Normal University State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric Physics Chinese Academy of Sciences

Globally, soil is the largest terrestrial carbon(C) reservoir. Robust quantification of soil organic C(SOC) stocks in existing global observation-based estimates avails accurate predictions in carbon-climate feedbacks and future climate trends. We investigated the magnitudes and distributions of global and regional SOC estimates(i.e., density and stocks) based on five widely used global gridded SOC datasets, a regional permafrost dataset developed in 2021(UM2021), and a global-scale soil profile database(World Soil Information Service) reporting measurements of a series of physical and chemical edaphic attributes. The five global gridded SOC datasets were the Harmonized World Soil Database(HWSD), World Inventory of Soil Emission Potentials at 30 arc-second resolution(WISE30sec), Global Soil Dataset for Earth System Models(GSDE), Global Gridded Soil Information at 250-m resolution(SoilGrids250m), and Global Soil Organic Carbon Map(GSOCmap). Our analyses showed that the magnitude and distribution of SOC varied widely among datasets, with certain datasets showing region-specific robustness. At the global scale, SOC stocks at the top 30 and 100 cm were estimated to be 828(range: 577–1 171) and 1 873(range: 1 086–2 678) Pg C, respectively. The estimates from GSDE, GSOCmap, and WISE30sec were comparable, and those of SoilGrids250m and HWSD were at the upper and lower ends. The spatial SOC distribution varied greatly among datasets, especially in the northern circumpolar and Tibetan Plateau permafrost regions. Regionally, UM2021 and WISE30sec performed well in the northern circumpolar permafrost regions,and GSDE performed well in China. The estimates of SOC by different datasets also showed large variabilities across different soil layers and biomes. The discrepancies were generally smaller for the 0–30 cm soil than the 0–100 cm soil. The datasets demonstrated relatively higher agreement in grasslands,croplands, and shrublands/savannas than in other biomes(e.g., wetlands).

关键词： biome carbon cycle Earth System Models permafrost region soil dataset soil map

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Emerging structures and dynamic mechanisms ofγ-secretase for Alzheimer’s disease

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Neural Regeneration Research 2025年第1期20卷 174-180页

作者： Yinglong Miao Michael S.Wolfe computational Medicine Program and Department of Pharmacology University of North Carolina–Chapel HillChapel HillNCUSA Department of Medicinal Chemistry University of KansasLawrenceKSUSA

γ-Secretase,called“the proteasome of the membrane,”is a membrane-embedded protease complex that cleaves 150+peptide substrates with central roles in biology and medicine,including amyloid precursor protein and the Notch family of cell-surface *** inγ-secretase and amyloid precursor protein lead to early-onset familial Alzheimer’s disease.γ-Secretase has thus served as a critical drug target for treating familial Alzheimer’s disease and the more common late-onset Alzheimer’s disease as ***,critical gaps remain in understanding the mechanisms of processive proteolysis of substrates,the effects of familial Alzheimer’s disease mutations,and allosteric modulation of substrate cleavage byγ-*** this review,we focus on recent studies of structural dynamic mechanisms ofγ-*** mechanisms,including the“Fit-Stay-Trim,”“Sliding-Unwinding,”and“Tilting-Unwinding,”have been proposed for substrate proteolysis of amyloid precursor protein byγ-secretase based on all-atom molecular dynamics *** an incorrect registry of the Notch1 substrate was identified in the cryo-electron microscopy structure of Notch1-boundγ-secretase,molecular dynamics simulations on a resolved model of Notch1-boundγ-secretase that was reconstructed using the amyloid precursor protein-boundγ-secretase as a template successfully capturedγ-secretase activation for proper cleavages of both wildtype and mutant Notch,being consistent with biochemical experimental *** approach could be potentially applied to decipher the processing mechanisms of various substrates byγ-*** addition,controversy over the effects of familial Alzheimer’s disease mutations,particularly the issue of whether they stabilize or destabilizeγ-secretase-substrate complexes,is ***,an outlook is provided for future studies ofγ-secretase,including pathways of substrate binding and product release,effects of modulators on familial Alzheimer’s disease mutations

关键词： Alzheimer’s disease amyloid precursor protein cryo-EM structures drug design intramembrane proteolysis molecular dynamics Notch

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The OsWRKY72-OsAAT30/OsGSTU26 module mediates reactive oxygen species scavenging to drive heterosis for salt tolerance in hybrid rice

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Journal of Integrative Plant biology 2024年第4期66卷 709-730页

作者： Citao Liu Bigang Mao Yanxia Zhang Lei tian Biao Ma Zhuo Chen Zhongwei Wei Aifu Li Ye Shao Gongye Cheng Lingling Li Wenyu Li Di Zhang Xiaoping Ding Jiangxiang Peng Yulin Peng Jiwai He Nenghui Ye Dingyang Yuan Chengcai Chu Meijuan Duan Hunan Provincial Key Laboratory of Stress biology College of AgricultureHunan Agricultural UniversityChangsha 410128China State Key Laboratory of Hybrid Rice Hunan Hybrid Rice Research CenterChangsha 410125China College of Agriculture South China Agricultural UniversityGuangzhou 510642China State Key Laboratory of Wheat and Maize Crop Science Center for Crop Genome EngineeringCollege of AgronomyHenan Agricultural UniversityZhengzhou 450002China College of Horticulture Fujian Agriculture and Forestry UniversityFuzhou 350002China Department of computational Medicine and Bioinformatics University of MichiganAnn ArborMI 48109 USA Biobin Data Science Co. Ltd.Changsha 410221China

Hybrid rice(Oryza sativa)generally outperforms its inbred parents in yield and stress tolerance,a phenomenon termed heterosis,but the underlying mechanism is not completely ***,we combined transcriptome,proteome,physiological,and heterosis analyses to examine the salt response of super hybrid rice Chaoyou1000(CY1000).In addition to surpassing the mean values for its two parents(mid-parent heterosis),CY1000 exhibited a higher reactive oxygen species scavenging ability than both its parents(over-parent heterosis or heterobeltiosis).Nonadditive expression and allele-specific gene expression assays showed that the glutathione S-transferase gene OsGSTU26 and the amino acid transporter gene OsAAT30 may have major roles in heterosis for salt tolerance,acting in an overdominant fashion in ***,we identified OsWRKY72 as a common transcription factor that binds and regulates OsGSTU26 and *** salt-sensitive phenotypes were associated with the OsWRKY72^(paternal)genotype or the OsAAT30^(maternal)genotype in core rice germplasm ***72^(paternal)specifically repressed the expression of OsGSTU26 under salt stress,leading to salinity sensitivity,while OsWRKY72^(maternal)specifically repressed OsAAT30,resulting in salinity *** results suggest that the OsWRKY72-OsAAT30/OsGSTU26 module may play an important role in heterosis for salt tolerance in an overdominant fashion in CY1000 hybrid rice,providing valuable clues to elucidate the mechanism of heterosis for salinity tolerance in hybrid rice.

关键词： allele-specific gene expression(ASE) heterosis hybrid rice nonadditive effect(NAE) salt tolerance transcriptome and proteome

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Molecular bases of morphologically diffused tumors across multiple cancer types

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National Science Review 2022年第11期9卷 65-67页

作者： Dingyun Liu Feiyang Xing Yueying Wang Jun Xiao Zheng An Ying Xu College of Computer Science and Technology Jilin University Center for Cancer systems biology China-Japan Union Hospital of Jilin University School of Life Sciences Jilin University China computational systems biology Lab Department of Biochemistry and Molecular Biology and Institute of BioinformaticsUniversity of Georgia

Diffuse gastric cancer (DGC) and intestinal gastric cancer (IGC) are the two main gastric cancer subtypes [1]. Morphologically, DGC consists of numerous disjoint tiny tumors while IGC forms one or a few solid tumors (Supplementary Supplementary Fig. S1)[1,2]. In-depth studies have discovered that DGCs generally have an ill-defined or missing glandular structure and reduced cell–cell adhesion,

关键词： identification enantioselective semisynthesis (−)-anisomelic acid oral agent anti-SARS-CoV-2

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Fundamental Boolean network modelling for childhood acute lymphoblastic leukaemia pathways

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Quantitative biology 2022年第1期10卷 94-121页

作者： Leshi Chen Don Kulasiri Sandhya Samarasinghe computational systems biology Laboratory Centre for Advanced Computational Solutions(C-fACS)Lincoln UniversityLincolnCanterbury 7647New Zealand Integrated systems Modelling Group Centre for Advanced Computational Solutions(C-fACS)Lincoln UniversityLincolnCanterbury 7647New Zealand

Background:A novel data-driven Boolean model,namely,the fundamental Boolean model(FBM),has been proposed to draw genetic regulatory insights into gene activation,inhibition,and protein decay,published in *** novel Boolean model facilitates the analysis of the activation and inhibition ***,the novel model does not handle the situation well,where genetic regulation might require more time steps to ***:Here,we propose extending the fundamental Boolean modelling to address the issue that some gene regulations might require more time steps to complete than *** denoted this extension model as the temporal fundamental Boolean model(TFBM)and related networks as the temporal fundamental Boolean networks(TFBNs).The leukaemia microarray datasets downloaded from the National Centre for Biotechnology Information have been adopted to demonstrate the utility of the proposed TFBM and ***:We developed the TFBNs that contain 285 components and 2775 Boolean rules based on TFBM on the leukaemia microarray datasets,which are in the form of short-time *** data contain gene expression measurements for 13 GC-sensitive children under therapy for acute lymphoblastic leukaemia,and each sample has three time points:0 hour(before GC treatment),6/8 hours(after GC treatment)and 24 hours(after GC treatment).Conclusion:We conclude that the proposed TFBM unlocks their predecessor’s limitation,Le.,FBM,that could help pharmaceutical agents identify any side effects on clinic-related *** hypotheses could be identified by analysing the extracted fundamental Boolean networks and analysing their up-regulatory and down-regulatory pathways.

关键词： Boolean modelling Boolean network time series data network inference data-driven boolean modelling fundamental boolean model fundamental boolean networks orchard cube

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Application of computational biology to Decode Brain Transcriptomes

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Genomics, Proteomics & Bioinformatics 2019年第4期17卷 367-380页

作者： Jie Li Guang-Zhong Wang CAS Key Laboratory of computational biology CAS-MPG Partner Institute for Computational BiologyShanghai Institute of Nutrition and HealthShanghai Institutes for Biological SciencesChinese Academy of SciencesShanghai 200031China University of Chinese Academy of Sciences Beijing 100049China

The rapid development of high-throughput sequencing technologies has generated massive valuable brain transcriptome atlases,providing great opportunities for systematically investigating gene expression characteristics across various brain regions throughout a series of developmental *** studies have revealed that the transcriptional architecture is the key to interpreting the molecular mechanisms of brain ***,our knowledge of brain transcriptional characteristics remains very *** the immense efforts to generate high-quality brain transcriptome atlases,new computational approaches to analyze these highdimensional multivariate data are greatly *** this review,we summarize some public resources for brain transcriptome atlases and discuss the general computational pipelines that are commonly used in this field,which would aid in making new discoveries in brain development and disorders.

关键词： Brain transcriptome atlas computational analysis Spatiotemporal pattern Coexpression analysis Single-cell analysis

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Convergent Usage of Amino Acids in Human Cancers as A Reversed Process of Tissue Development

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Genomics, Proteomics & Bioinformatics 2022年第1期20卷 147-162页

作者： Yikai Luo Han Liang Graduate Program in Quantitative and computational Biosciences Baylor College of MedicineHoustonTX 77030USA Department of Bioinformatics and computational biology The University of Texas MD Anderson Cancer CenterHoustonTX 77030USA Department of systems biology The University of Texas MD Anderson Cancer CenterHoustonTX 77030USA

Genome-and transcriptome-wide amino acid usage preference across different species is a well-studied phenomenon in molecular evolution,but its characteristics and implication in cancer evolution and therapy remain largely ***,we analyzed large-scale transcriptome/proteome profiles,such as The Cancer Genome Atlas(TCGA),the Genotype-Tissue Expression(GTEx),and the Clinical Proteomic Tumor Analysis Consortium(CPTAC),and found that compared to normal tissues,different cancer types showed a convergent pattern toward using biosynthetically low-cost amino *** a pattern can be accurately captured by a single index based on the average biosynthetic energy cost of amino acids,termed energy cost per amino acid(ECPA).With this index,we further compared the trends of amino acid usage and the contributing genes in cancer and tissue development,and revealed their reversed ***,focusing on the liver,a tissue with a dramatic increase in ECPA during development,we found that ECPA represents a powerful biomarker that could distinguish liver tumors from normal liver samples consistently across 11 independent patient cohorts and outperforms any index based on single *** study reveals an important principle underlying cancer evolution and suggests the global amino acid usage as a system-level biomarker for cancer diagnosis.

关键词： Amino acid usage Tissue development Biosynthetic energy Diagnostic biomarker

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A computational model to identify fertility-related proteins using sequence information

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Frontiers of Computer Science 2024年第1期18卷 229-237页

作者： Yan LIN Jiashu WANG Xiaowei LIU Xueqin XIE De WU Junjie ZHANG Hui DING Key Laboratory for Animal Disease-Resistance Nutrition of the Ministry of Agriculture Animal Nutrition InstituteSichuan Agricultural UniversityChengdu 611130China School of Life Science and Technology and Center for Informational biology University of Electronic Science and Technology of ChinaChengdu 610054China

Fertility is the most crucial step in the development process,which is controlled by many fertility-related proteins,including spermatogenesis-,oogenesis-and embryogenesis-related *** identification of fertility-related proteins can provide important clues for studying the role of these proteins in ***,in this study,we constructed a two-layer classifier to identify fertility-related *** this classifier,we first used the composition of amino acids(AA)and their physical and chemical properties to code these three fertility-related ***,the feature set is optimized by analysis of variance(ANOVA)and incremental feature selection(IFS)to obtain the optimal feature *** five-fold cross-validation(CV)and independent data tests,the performance of models constructed by different machine learning(ML)methods is evaluated and ***,based on support vector machine(SVM),we obtained a two-layer model to classify three fertility-related *** the independent test data set,the accuracy(ACC)and the area under the receiver operating characteristic curve(AUC)of the first layer classifier are 81.95%and 0.89,respectively,and them of the second layer classifier are 84.74%and 0.90,*** results show that the proposed model has stable performance and satisfactory prediction accuracy,and can become a powerful model to identify more fertility related proteins.

关键词： sfertility-related proteins machine1 learning sequence information feature selection

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Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles

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npj computational Materials 2023年第1期9卷 49-59页

作者： Aik Rui Tan Shingo Urata Samuel Goldman Johannes C.B.Dietschreit Rafael Gómez-Bombarelli Department of Materials Science and Engineering Massachusetts Institute of TechnologyCambridgeMAUSA Innovative Technology Laboratories AGC IncTokyoJapan computational and systems biology Massachusetts Institute of TechnologyCambridgeMAUSA

Neural networks(NNs)often assign high confidence to their predictions,even for points far out of distribution,making uncertainty quantification(UQ)a *** they are employed to model interatomic potentials in materials systems,this problem leads to unphysical structures that disrupt simulations,or to biased statistics and dynamics that do not reflect the true *** UQ techniques can find new informative data and drive active learning loops for robust ***,a variety of UQ techniques,including newly developed ones,exist for atomistic simulations and there are no clear guidelines for which are most effective or suitable for a given *** this work,we examine multiple UQ schemes for improving the robustness of NN interatomic potentials(NNIPs)through active *** particular,we compare incumbent ensemble-based methods against strategies that use single,deterministic NNs:mean-variance estimation(MVE),deep evidential regression,and Gaussian mixture models(GMM).We explore three datasets ranging from in-domain interpolative learning to more extrapolative out-of-domain generalization challenges:rMD17,ammonia inversion,and bulk silica *** is measured across multiple metrics relating model error to *** experiments show that none of the methods consistently outperformed each other across the various *** remained better at generalization and for NNIP robustness;MVE only proved effective for in-domain interpolation,while GMM was better out-of-domain;and evidential regression,despite its promise,was not the preferable alternative in any of the *** broadly,cost-effective,single deterministic models cannot yet consistently match or outperform ensembling for uncertainty quantification in NNIPs.

关键词： ensemble evident neural

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Strain-promoted S-arylation and alkenylation of sulfinamides using arynes and cyclic alkynes

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Science China Chemistry 2024年第3期67卷 928-935页

作者： Xi Zou Boming Shen Gao-lin Li Qian Liang Yanhua Ouyang Binghe Yang Peiyuan Yu Bing Gao State Key Laboratory of Chemo/Bio-Sensing and Chemometrics College of Chemistry and Chemical EngineeringInstitute of Chemical Biology and NanomedicineHunan UniversityChangsha 410082China Department of Chemistry and Shenzhen Grubbs Institute Guangdong Provincial Key Laboratory of CatalysisSouthern University of Science and TechnologyShenzhen 518055China

The conversion of commercially available chiral sulfinamides into pharmaceutically useful chiral sulfoximines via direct SIVfunctionalization is synthetically attractive but challenging due to the competitive reaction of N-functionalization. Herein, we disclose a novel strain-release strategy to access stereospecific and chemoselective SIV-arylation and alkenylation of sulfinamides using arynes and strained cyclic alkynes. This method tolerates an unprecedented chemical diversity of functional groups attached to the nitrogen center(N-R). The origin of the high SIV-selectivity is elucidated by density functional theory calculations, suggesting a stepwise mechanism for the aryne substrates and a concerted mechanism for the cyclic alkynes.

关键词： arylation alkenylation sulfoximines sulfinamides arynes

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