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Background: Impact of radiotherapy (RT) for esophageal cancer (EC) patients on the development of secondary head and neck cancer (SHNC) remains equivocal. The objective of this study was to investigate the link between definitive RT used for EC treatment and subsequent SHNC. Methods: This study was conducted using the Surveillance, Epidemiology, and End Results (SEER) database to collect the data of primary EC patients. Fine-Gray competing risk regression and standardized incidence ratio (SIR) and propensity score matching (PSM) method were used to match SHNC patients with only primary head and neck cancer (HNC) patients. Overall survival (OS) rates were applied by Kaplan-Meier analysis. Results: In total, 14,158 EC patients from the SEER database were included, of which 9,239 patients (65.3%) received RT and 4,919 patients (34.7%) received no radiation therapy (NRT). After a 12-month latency period, 110 patients (1.2%) in the RT group and 36 patients (0.7%) in the NRT group experienced the development of SHNC. In individuals with primary EC, there was an increased incidence of SHNC compared to the general US population (SIR = 5.95, 95% confidence interval (CI): 5.15 - 6.84). Specifically, the SIR for SHNC was 8.04 (95% CI: 6.78 - 9.47) in the RT group and 3.51 (95% CI: 2.64 - 4.58) in the NRT group. Patients who developed SHNC after RT exhibited significantly lower OS compared to those after NRT. Following PSM, the OS of patients who developed SHNC after RT remained significantly lower than that of matched patients with only primary HNC. Conclusion: An association was discovered between RT for EC and increased long-term risk of SHNC. This work enables radiation oncologists to implement mitigation strategies to reduce the long-term risk of SHNC in patients who have received RT following primary EC.
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China's imports of livestock feed, particularly protein-rich feeds, pose challenges to global environmental sustainability. Achieving protein self-sufficiency for food and feed in China without exceeding environmental boundaries requires integrated measures and optimization of China's food system. Here we propose holistic food system innovation strategies consisting of three components-technological innovation, integrated spatial planning and demand-side options-to reduce protein import dependency and promote global environmental sustainability. We find that food system innovations can close almost 80% of China's future protein gaps while reducing 57-85% of agricultural import-embodied environmental impacts. Deploying these innovations would also reduce greenhouse gas emissions (22-27%) and people's harmful exposure to ammonia (73-81%) compared with the baseline scenario in 2050. Technological innovations play a key role in closing protein gaps, while integrated crop-livestock spatial planning is imperative for achieving environmental and health targets.
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Proteínas Alimentares , China , Humanos , Animais , Abastecimento de Alimentos , Meio Ambiente , Gado , Agricultura , Ração Animal/análise , Conservação dos Recursos Naturais , Produtos Agrícolas , Gases de Efeito Estufa/efeitos adversosRESUMO
Global warming modulates soil respiration (RS) via microbial decomposition, which is seasonally dependent. Yet, the magnitude and direction of this modulation remain unclear, partly owing to the lack of knowledge on how microorganisms respond to seasonal changes. Here, we investigated the temporal dynamics of soil microbial communities over 12 consecutive months under experimental warming in a tallgrass prairie ecosystem. The interplay between warming and time altered (P < 0.05) the taxonomic and functional compositions of microbial communities. During the cool months (January to February and October to December), warming induced a soil microbiome with a higher genomic potential for carbon decomposition, community-level ribosomal RNA operon (rrn) copy numbers, and microbial metabolic quotients, suggesting that warming stimulated fast-growing microorganisms that enhanced carbon decomposition. Modeling analyses further showed that warming reduced the temperature sensitivity of microbial carbon use efficiency (CUE) by 28.7% when monthly average temperature was low, resulting in lower microbial CUE and higher heterotrophic respiration (Rh) potentials. Structural equation modeling showed that warming modulated both Rh and RS directly by altering soil temperature and indirectly by influencing microbial community traits, soil moisture, nitrate content, soil pH, and gross primary productivity. The modulation of Rh by warming was more pronounced in cooler months compared to warmer ones. Together, our findings reveal distinct warming-induced effects on microbial functional traits in cool months, challenging the norm of soil sampling only in the peak growing season, and advancing our mechanistic understanding of the seasonal pattern of RS and Rh sensitivity to warming.
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Pradaria , Microbiota , Estações do Ano , Microbiologia do Solo , Solo , Solo/química , Aquecimento Global , Bactérias/classificação , Bactérias/genética , Bactérias/isolamento & purificação , Bactérias/metabolismo , Carbono/metabolismo , Carbono/análise , TemperaturaRESUMO
Polycyclic aromatic hydrocarbons (PAHs) and carbon dioxide primarily originate from the combustion of fossil fuels and biomass. The implementation of the Chinese "double carbon strategy" is expected to impact the distribution of PAH emissions, consequently influencing the spatial distribution trend of PAHs in surface soil. Therefore, it is crucial to quantitatively evaluate the effectiveness of the Chinese "double carbon strategy" on soil PAH pollution for the purpose of "the reduction of pollution and carbon emissions". This study utilized 15,088 individual PAH concentration data from 943 soil samples collected between 2003 and 2020 in China, in conjunction with PAH emissions at a 10 km resolution, for meta-analysis. The calculated PAH emissions in this study are in line with the global PAH emission inventory (PKU-PAH-2007), with a relative standard deviation at the provincial level of less than 25 %. Subsequently, a novel method was developed using emission density and Kow of PAHs to predict PAH concentrations in surface soil based on a least-squares regression model. Compared to other environmental models, the method established in this study significantly reduced the percent sample deviation to less than 70 %. Furthermore, energy consumption data for China were simulated based on the implementation plan of the "double carbon strategy" to project PAH emissions and soil PAH levels for the years 2030 and 2060. The predicted PAH emissions in China were estimated to decrease to 41,300 t in 2030 and 10,406.5 t in 2060 from 78,815 t in 2020. Moreover, the heavily contaminated areas of soil PAHs (i.e., total PAH concentrations in soil exceeding 1000 µg kg-1) were projected to decrease by 45 % and 82 % in 2030 and 2060, respectively, compared to levels in 2020. These findings suggest that the implementation of the "double carbon strategy" can fundamentally reduce the pollution of PAHs in surface soil of China.
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Hidrocarbonetos Policíclicos Aromáticos , Poluentes do Solo , Hidrocarbonetos Policíclicos Aromáticos/análise , China , Poluentes do Solo/análise , Monitoramento Ambiental/métodos , Solo/química , Poluição Ambiental , Carbono/análise , Dióxido de Carbono/análise , População do Leste AsiáticoRESUMO
The diffusion model is used to calculate both the time-averaged flow of particles in stochastic media and the propagation of waves averaged over ensembles of disordered static configurations. For classical waves exciting static disordered samples, such as a layer of paint or a tissue sample, the flux transmitted through the sample may be dramatically enhanced or suppressed relative to predictions of diffusion theory when the sample is excited by a waveform corresponding to a transmission eigenchannel. Even so, it is widely assumed that the velocity of waves is irretrievably randomized in scattering media. Here we demonstrate in microwave measurements and numerical simulations that the statistics of velocity of different transmission eigenchannels are distinct and remains so on all length scales and are identical on the incident and output surfaces. The interplay between eigenchannel velocities and transmission eigenvalues determines the energy density within the medium, the diffusion coefficient, and the dynamics of propagation. The diffusion coefficient and all scattering parameters, including the scattering mean free path, oscillate with the width of the sample as the number and shape of the propagating channels in the medium change.
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Background: Nonalcoholic steatohepatitis (NASH) is the advanced stage of nonalcoholic fatty liver disease (NAFLD), one of the most prevalent chronic liver diseases. The effectiveness of bariatric surgery in treating NASH and preventing or even reversing liver fibrosis has been demonstrated in numerous clinical studies, but the underlying mechanisms and crucial variables remain unknown. Methods: Using the GSE135251 dataset, we examined the gene expression levels of NASH and healthy livers. Then, the differentially expressed genes (DEGs) of patients with NASH, at baseline and one year after bariatric surgery, were identified in GSE83452. We overlapped the hub genes performed by protein-protein interaction (PPI) networks and DEGs with different expression trends in both datasets to obtain key genes. Genomic enrichment analysis (GSEA) and genomic variation analysis (GSVA) were performed to search for signaling pathways of key genes. Meanwhile, key molecules that regulate the key genes are found through the construction of the ceRNA network. NASH mice were induced by a high-fat diet (HFD) and underwent sleeve gastrectomy (SG). We then cross-linked the DEGs in clinical and animal samples using quantitative polymerase chain reaction (qPCR) and validated the key genes. Results: Seven key genes (FASN, SCD, CD68, HMGCS1, SQLE, CXCL10, IGF1) with different expression trends in GSE135251 and GSE83452 were obtained with the top 30 hub genes selected by PPI. The expression of seven key genes in mice after SG was validated by qPCR. Combined with the qPCR results from NASH mice, the four genes FASN, SCD, HMGCS1, and CXCL10 are consistent with the biological analysis. The GSEA results showed that the 'cholesterol homeostasis' pathway was enriched in the FASN, SCD, HMGCS1, and SQLE high-expression groups. The high-expression groups of CD68 and CXCL10 were extremely enriched in inflammation-related pathways. The construction of the ceRNA network obtained microRNAs and ceRNAs that can regulate seven key genes expression. Conclusion: In summary, this study contributes to our understanding of the mechanisms by which bariatric surgery improves NASH, and to the development of potential biomarkers for the treatment of NASH.
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Cirurgia Bariátrica , MicroRNAs , Hepatopatia Gordurosa não Alcoólica , Humanos , Animais , Camundongos , Hepatopatia Gordurosa não Alcoólica/genética , Hepatopatia Gordurosa não Alcoólica/cirurgia , MicroRNAs/genética , Mapas de Interação de ProteínasRESUMO
Singlet oxygen (1O2) is a reactive species for the selective degradation of stubborn organic pollutants. Given its resistance to harsh water environment, the effective and exclusive generation of 1O2 is acknowledged as a key strategy to mitigate water production costs and ensure water supply safety. Herein, we synthesized MnOx intercalated MnFe layered double hydroxides (MF-MnOx) to selectively produce 1O2 through the activation of PMS. The distinctive confined structure endowed MF-MnOx with a special pathway for the PMS activation. The direct oxidation of BPA on the intercalated MnOx induced the charge imbalance in the MnFe-LDH layer, resulting in the selective generation of 1O2. Moreover, acceptable activity deterioration of MF-MnOx was observed in a 10 h continuous degradation test in actual water, substantiating the application potential of MF-MnOx. This work presents a novel catalyst for the selective production of 1O2, and evaluates its prospects in the remediation of micro-polluted water.
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Peróxidos , Oxigênio Singlete , Oxigênio Singlete/química , Peróxidos/química , Hidróxidos/química , Água , OxigênioRESUMO
The Eurasian steppe is the largest temperate grassland in the world. The grassland of the Mongolian Plateau (MP) represents an important part of the Eurasian steppe with high climatic sensitivity. Gross primary productivity (GPP) is a key indicator of the grassland's production, status and dynamic on the MP. In this study, we calibrated and evaluated the grassland-specific light use efficiency model (GRASS-LUE) against the observed GPP collected from nine eddy covariance flux sites on the MP, and compared the performance with other four GPP products (MOD17, VPM, GLASS and GOSIF). GRASS-LUE with higher R2 (0.91) and lower root mean square error (RMSE = 0.99 gC m-2 day-1) showed a better performance compared to the four GPP products in terms of model accuracy and dynamic consistency, especially in typical and desert steppe. The parameters of the GRASS-LUE are more suitable for water-limited grassland could be the reason for its outstanding performance in typical and desert steppe. Mean grassland GPP derived from GRASS-LUE was higher in the east and lower in the west of the MP. Grassland GPP was on average 205 gC m-2 over the MP between 2001 and 2020 with mean annual total GPP of 322 TgC yr-1. 30 % of the MP steppe showed a significant GPP increase. Growing season precipitation is the main factor affecting GPP of the MP steppe across regions. Anthropogenic factors (livestock density and population density) had greater effect on GPP than growing season temperature in pastoral counties in IM that take grazing as one of main industries. These findings can inform the status and trend of the productivity of MP steppe and help government and scientific research institutions to understand the drivers for spatial pattern of grassland GPP on the MP.
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The material properties and volume proportion of the fibers as well as the cross-sectional area proportion of nucleus pulposus vary greatly in different studies. The effect of these factors on the mechanical behavior of intervertebral discs (IVDs) are uncertain. The IVDs finite element models with different parameters were created to investigate the pressure, height, rotation, stress, and strain of the IVDs under loads: pure compression, rotation after compression or axial moment after compression. The results showed that the material properties of fibers had great impact on the mechanical behavior of IVDs, especially on the rotation angle. When the fiber volume ratio was small, its changes had a significant impact on the rotation angle of the IVDs. The area proportions of nucleus pulposus had relatively little effect on the mechanical behavior of IVDs. The IVDs rotation should be observed when validating the model. By adjusting the elastic modulus or volume ratio of fibers within a reasonable range, a model that could simulate the mechanical behavior of normal IVDs could be obtained. It was reasonable to make the area proportion of nucleus pulposus within 25%-50% for the IVDs finite element model. This study provides guidance and reference for finite element modeling of the IVDs and the investigation of the IVDs degeneration mechanism.
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Degeneração do Disco Intervertebral , Disco Intervertebral , Núcleo Pulposo , Humanos , Módulo de Elasticidade , Pressão , Estresse Mecânico , Fenômenos BiomecânicosRESUMO
Although numerous studies have reported the influencing factors of polycyclic aromatic hydrocarbons (PAHs) in surface soil from source, process or soil perspectives, the mechanism of PAHs heterogeneity in surface soil are still not well understood. In this study, the effects of 16 PAHs in surface soil of China sampled between 2003 and 2020 with their 17 "source-process-sink" factors at 1 km resolution (N = 660)) were explored using deep learning (eXtreme Gradient Boosting) to mine key information from complex dataset under the optimized parameters (i.e., learning rate = 0.05, maximum depth = 5, sub-sample = 0.8). It was observed that top five factors of 16 PAH had the largest cumulative contribution (i.e., from 84.8% to 98.1%) on their soil concentrations. PAH emission was the predominant driver, and its effect on soil PAH increases with increasing logKow. Soil was the second driver, in which clay can promote the partition of PAHs with low or middle logKow. However, sand can accumulate those congeners with high logKow. Moreover, the deep learning plus geo-statistical models (with low deviation for testing dataset (N = 283)) were capable of predicting soil PAH concentrations using their drivers with high accuracy. This study improved the understanding of the environmental fate and spatial variability of soil PAHs, as well as provided a novel technique (i.e., deep learning coupled with geo-statistics) for accurate prediction of soil pollutants.
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The high expression or mutation of SHP2 can induce cancer, so targeting SHP2 has become a new strategy for cancer treatment. In this study, we used the previously reported SHP2 allosteric inhibitor IACS-13909 as a lead drug for structural derivation and modification, and synthesized three SHP2 inhibitors. Among them, 1H-pyrazolo[3,4-b]pyrazine derivative 4b was a highly selective SHP2 allosteric inhibitor, with an IC50 value of 3.2 nM, and its inhibitory activity was 17.75 times than that of the positive control IACS-13909. The cell proliferation experiment detected that compound 4b would markedly inhibit the proliferation of various cancer cells. Interestingly, compound 4b was highly sensitive to KRASG12C-mutant non-small cell lung cancer NCI-H358 cells, with an IC50 value of 0.58 µM and its antiproliferative activity was 4.79 times than that of IACS-13909. Furthermore, the combination therapy of compound 4b and KRASG12C inhibitor sotorasib would play a strong synergistic effect against NCI-H358 cells. The western blot experiment detected that compound 4b markedly downregulated the phosphorylation levels of ERK and AKT in NCI-H358 cells. Molecular docking study predicted that compound 4b bound to the allosteric site of SHP2 and formed H-bond interactions with key residues Thr108, Glu110, Arg111, and Phe113. In summary, this study aims to provide new ideas for the development of SHP2 allosteric inhibitors for the treatment of KRASG12C mutant non-small cell lung cancer.Communicated by Ramaswamy H. Sarma.
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Co-optimization of multiple management practices may facilitate climate-smart agriculture, but is challenged by complex climate-crop-soil management interconnections across space and over time. Here we develop a hybrid approach combining agricultural system modelling, machine learning and life cycle assessment to spatiotemporally co-optimize fertilizer application, irrigation and residue management to achieve yield potential of wheat and maize and minimize greenhouse gas emissions in the North China Plain. We found that the optimal fertilizer application rate and irrigation for the historical period (1995-2014) are lower than local farmers' practices as well as trial-derived recommendations. With the optimized practices, the projected annual requirement of fertilizer, irrigation water and residue inputs across the North China Plain in the period 2051-2070 is reduced by 16% (14-21%) (mean with 95% confidence interval), 19% (7-32%) and 20% (16-26%), respectively, compared with the current supposed optimal management in the historical reference period, with substantial greenhouse gas emission reductions. We demonstrate the potential of spatiotemporal co-optimization of multiple management practices and present digital mapping of management practices as a benchmark for site-specific management across the region.
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Gases de Efeito Estufa , Fertilizantes/análise , Produtos Agrícolas , Agricultura , Produção AgrícolaRESUMO
BACKGROUND: Ubiquitination, small ubiquitin-related modifiers, and NEDDylation are now found to function in cancer biology; however, its role in the oral cancer patients remains unclear. METHODS: A set of bioinformatic tools was integrated to analyze the expression and prognostic significance of ubiquitin and ubiquitin-like (UB/UBL) genes. A UB/UBL-related risk score was developed via correlation analyses, univariate Cox regression, and multivariate Cox regression. Nomogram analysis evaluates the model's prediction performance. The drug sensitivity analysis, immune profiles of UB/UBL-classified oral squamous cell carcinoma (OSCC) patients, and their related function pathway were investigated, and the role of UB/UBL-related genes in drug therapy was analyzed. RESULTS: A total of six prognostic UB/UBL-related genes were obtained. PSMD3, PCGF2, and H2BC10 were significantly downregulated in OSCC tissue and associated with longer survival time. OSCC patients in the high-risk group showed a significantly lower overall survival and enriched in cancer-related pathways. The prognostic potential of genes associated with UB/UBL was discovered, and patients with high-risk scores showed an increase of protumor immune infiltrates and a high expression of immune checkpoints. Moreover, the area under the curve of the annual survival rate was 0.616, 0.671, and 0.673, respectively. Besides, patients in the high-risk group are more sensitive to docetaxel, doxorubicin, and methotrexate therapy. CONCLUSIONS: We construct a prognosis model for OSCC patients with UB/UBL-related genes and try to find a new approach to treating oral cancer patients. The UB/UBL-related signature is helpful in developing new tumor markers, prognostic prediction, and in guiding treatment for OSCC patients.
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Carcinoma de Células Escamosas , Neoplasias de Cabeça e Pescoço , Neoplasias Bucais , Humanos , Carcinoma de Células Escamosas de Cabeça e Pescoço/genética , Carcinoma de Células Escamosas/tratamento farmacológico , Carcinoma de Células Escamosas/genética , Prognóstico , Sumoilação , Neoplasias Bucais/genética , Ubiquitinação , Ubiquitina/metabolismo , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/metabolismoRESUMO
Reactions of reactive halogen species (Clâ¢, Brâ¢, and Cl2â¢-) with trace organic contaminants (TrOCs) have received much attention in recent years, and their k values are fundamental parameters for understanding their reaction mechanisms. However, k values are usually unknown. In this study, we developed machine learning (ML)-based quantitative structure-activity relationship (QSAR) models to predict k values. We tested five algorithms, namely, random forest, neural network, XGBoost, support vector machine (SVM), and multilinear regression, using molecular descriptors (MDs) and molecular fingerprints (MFs) as inputs. The optimal algorithms were MD-XGBoost for Cl⢠and Brâ¢, and MF-SVM for Cl2â¢-, respectively, with R2test values of 0.876, 0.743, and 0.853. We found that electron-withdrawing/donating groups tended to interfere with the reactivity of Cl2â¢- more than Cl⢠and Brâ¢. This explains why MFs are better inputs for predictive models of Cl2â¢-, whereas MDs are more suitable for Cl⢠and Brâ¢. Furthermore, we interpreted the models using SHAP analysis, and the results indicated that our models accurately predicted k values both statistically and mechanistically. Our models provide useful tools for obtaining unknown k values and help researchers understand the inherent relationships between the models.
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Algoritmos , Halogênios , Aprendizado de Máquina , Redes Neurais de Computação , Algoritmo Florestas Aleatórias , Relação Quantitativa Estrutura-AtividadeRESUMO
Two new triterpenoids (1-2), along with six known analogues (3-8) were obtained from the dried whole plant of Leptopus clarkei. Compound 1 is a 3,4-seco-lupane-type triterpenoid, and compound 2 is a phenylpropanoid-conjugated pentacyclic triterpenoid possessing trans-p-coumaroyl unit attached to oleanane-type skeleton. This is the first report on chemical investigation of the L. clarkei, and the triterpenoid derivatives were found in this plant for the first time. The structures of the new compounds were unequivocally elucidated by HRESIMS and 1D/2D NMR data. Additionally, the isolated compounds were evaluated for theircytotoxicities against four cancer cell lines including HepG2, MCF-7, A549 and HeLa. Notably, compound 2 exhibited the most significant antiproliferative activity with IC50 less than 20â µM for four cancer lines.
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Antineoplásicos Fitogênicos , Neoplasias , Triterpenos , Humanos , Triterpenos/farmacologia , Triterpenos/química , Espectroscopia de Ressonância Magnética , Extratos Vegetais/química , Células HeLa , Estrutura Molecular , Antineoplásicos Fitogênicos/farmacologia , Antineoplásicos Fitogênicos/química , Neoplasias/tratamento farmacológicoRESUMO
The critical prerequisite for the prevention and control of soil heavy metal (HM) pollution is the identification of factors that influence soil HM accumulation. The dominant factors have been individually identified and apportioned in existing studies. However, the accumulation of soil HMs results from a combination of multiple factors, and the influence of a single factor is less than the interaction of multiple parameters on soil HM pollution. In this study, we employed Geodetector to delve into the interaction effect of the influencing factors on the variations of soil HMs. We performed partial dependence plot to depict how these factors interact with each other to affect the HM content. We found that both individually and interactively, pH and agricultural activities significantly impact soil HM content. Except for Hg and Cu, the pairs with the most significant interaction effects all involve pH. For Pb, As and Zn, interaction with pH has the most significant driving force compared to the other factors. For Cu, Hg, and Ni, all environmental factor interactions increased their explanatory power, while for Cr, the single most significant driver decreased its driving power when interacting with other factors. Additionally, the study area exhibited a widespread prevalence of changes in HM concentration being governed by the synergistic effect of two factors. For the response of HMs to the interaction of pH and fertilizer, soil HM concentration was sensitive to pH, while fertilizer had less effect. These results provide a dependable method of investigating the interaction of environmental factors on soil HM content and put forth efficacious and potent tactical measures for soil HM pollution prevention and control based on the interaction type.