Net greenhouse gas balance in U.S. croplands: How can soils be part of the climate solution?

Agricultural soils play a dual role in regulating the Earth's climate by releasing or sequestering carbon dioxide (CO2 ) in soil organic carbon (SOC) and emitting non-CO2 greenhouse gases (GHGs) such as nitrous oxide (N2 O) and methane (CH4 ). To understand how agricultural soils can play a role in climate solutions requires a comprehensive assessment of net soil GHG balance (i.e., sum of SOC-sequestered CO2 and non-CO2 GHG emissions) and the underlying controls. Herein, we used a model-data integration approach to understand and quantify how natural and anthropogenic factors have affected the magnitude and spatiotemporal variations of the net soil GHG balance in U.S. croplands during 1960-2018. Specifically, we used the dynamic land ecosystem model for regional simulations and used field observations of SOC sequestration rates and N2 O and CH4 emissions to calibrate, validate, and corroborate model simulations. Results show that U.S. agricultural soils sequestered 13.2 ± 1.16 $$ 13.2\pm 1.16 $$ Tg CO2 -C year-1 in SOC (at a depth of 3.5 m) during 1960-2018 and emitted 0.39 ± 0.02 $$ 0.39\pm 0.02 $$ Tg N2 O-N year-1 and 0.21 ± 0.01 $$ 0.21\pm 0.01 $$ Tg CH4 -C year-1 , respectively. Based on the GWP100 metric (global warming potential on a 100-year time horizon), the estimated national net GHG emission rate from agricultural soils was 122.3 ± 11.46 $$ 122.3\pm 11.46 $$ Tg CO2 -eq year-1 , with the largest contribution from N2 O emissions. The sequestered SOC offset ~28% of the climate-warming effects resulting from non-CO2 GHG emissions, and this offsetting effect increased over time. Increased nitrogen fertilizer use was the dominant factor contributing to the increase in net GHG emissions during 1960-2018, explaining ~47% of total changes. In contrast, reduced cropland area, the adoption of agricultural conservation practices (e.g., reduced tillage), and rising atmospheric CO2 levels attenuated net GHG emissions from U.S. croplands. Improving management practices to mitigate N2 O emissions represents the biggest opportunity for achieving net-zero emissions in U.S. croplands. Our study highlights the importance of concurrently quantifying SOC-sequestered CO2 and non-CO2 GHG emissions for developing effective agricultural climate change mitigation measures.

Interference-induced generation of a chirp-free short isolated attosecond pulse in the water window region with multicolor laser fields.

Compensating for the intrinsic attosecond chirp (atto-chirp) of wideband high-order harmonics in the water window region is a significant challenge, in order to obtain isolated attosecond pulses (IAPs) with a width of tens of attoseconds (as). Here, we propose to realize the generation of IAP with duration as short as 20 as, central energy of 365 eV, and bandwidth exceeding 150 eV from chirp-free high harmonics generated by a four-color driving laser, without the necessity for atto-chirp compensation with natural materials. Unlike any other gating methods that an IAP arises from only one electron ionization event, we take advantage of the interference between harmonic radiation produced by multiple ionizing events. We further demonstrate that such chirp-free short IAP survives after taking account of macroscopic propagation effects. Given that the synthesized multicolor laser field can also effectively increase the harmonic flux, this work provides a practical way for experiments to generate the broad bandwidth chirp-free IAPs in the water window region.

Associations between insufficient sleep, skipping breakfast and depressive symptoms in children and adolescents: A school-based cross-sectional study in China.

OBJECTIVE: Insufficient sleep and skipping breakfast are increasingly prevalent among children and adolescents. Both behaviors are associated with the onset of depression. This study aims to examine the independent and joint associations of these two behaviors with depressive symptoms, and investigate whether these associations varied by age or sex. METHODS: The Center for Epidemiological Studies Depression Scale (CES-D) was used to evaluate the depressive symptoms. This cross-sectional study including 11,887 students aged 11-19 years using a stratified cluster, multistage sampling method in Ningbo, China. Multiple logistic regressions were conducted to evaluate the independent and joint association between insufficient sleep, skipping breakfast and depressive symptoms. Sensitivity analyses and stratified analyses by age and sex were performed using the same modelling strategies. RESULTS: The overall prevalence of depressive symptoms was 15.27%. Skipping breakfast (Odds Ratio (OR) = 2.557, 95% Confidence Interval (CI) = 2.236-2.925) and insufficient sleep (OR = 1.547, 95%CI = 1.390-1.723) was independently associated with depressive symptoms. Compared to students with "sufficient sleep and breakfast every day", the OR was 4.385 (95%CI = 3.649-5.271) for those with "insufficient sleep and skipping breakfast". Meanwhile, the joint association was moderated by age group, with a more apparent association observed in the 11-15-year-old group compared to the 16-19-year-old group. CONCLUSIONS: These findings indicated that insufficient sleep and skipping breakfast were independently and jointly associated with depressive symptoms. Insufficient sleep and skipping breakfast could be considered as two of the predictors of depression.

A biomarker panel of secondary hypertension is simultaneously quantified by coupling of magnetic solid-phase extraction and liquid chromatography-tandem mass spectrometry.

RATIONALE: Secondary hypertension is often caused by activation of complex multi-organ endocrine systems, while renin activity indicated by angiotensins (Angs), aldosterone (ALD) and cortisol (COR) in such systems are generally accepted as its diagnostic markers. As antibody-based methods cannot offer comparable quantification for these biomarkers, a liquid chromatography (LC)-tandem mass spectrometry (MS/MS)-based approach was developed to quantify them simultaneously and accurately. METHODS: Five different beads for magnetic solid-phase extraction (MSPE) were evaluated towards their enrichment efficiency for these biomarkers. An LC system with optimized elution gradient and a triple-quadrupole MS with tuned parameters were coupled to quantitatively monitor the extracted analytes. The method performance was further examined such as linearity, precision, stability, recovery rate and matrix effect. Based on the developed method, the abundance of Ang II, ALD and COR in plasma was measured and the quantification was compared with that derived from commercial ELISA kits. RESULTS: As compared with other MSPEs, Angs, ALD and COR were highly enriched by the HLB magnetic beads with satisfactory recoveries. These analytes were simultaneously quantified by LC/MS/MS and all the method parameters for quantification were well matched with the requirements of clinical testing. Comparison of the quantitative results derived from ELISA and LC/MS/MS exhibited that the two methods offered basically comparable values with Pearson r values at 0.896, 0.895 and 0.835, respectively. The stability test for plasma Angs at room temperature indicated that the abundance of Ang II was relatively stable within 3 h, whereas that of Ang I and Ang 1-7 was time-dependently changed. CONCLUSIONS: Coupling of HLB beads and LC/MS/MS thus enables simultaneous quantification of a set of biomarkers related to secondary hypertension.

Notoginsenoside R1 restrains the proliferation and migration of airway smooth muscle cells isolated from rats with chronic obstructive pulmonary disease.

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a common disorder that is characterized by systemic and lung inflammation. Notoginsenoside R1 (NGR1) displays anti-inflammatory properties in numerous diseases. We aimed to explore the function and mechanism of NGR1 in COPD. MATERIALS AND METHODS: COPD rats were established through cigarette smoke exposure, lipopolysaccharide injection, and cold stimulation. Rat airway smooth muscle cells (ASMCs) were separated and identified. Then, ASMCs were treated with NGR1 (25 or 50 µM) and cigarette smoke extract (CSE). Thereafter, the vitality, proliferation, and migration of ASMCs were measured. Additionally, cell cycle, inflammation-related factors, α-SMA, and PI3K/AKT pathway-related marker expressions of the ASMCs were also detected. Molecular docking experiments were conducted to explore the interaction of NGR1 to PI3K, TGF-ß, p65, and AKT. Moreover, 740 Y-P (a PI3K/Akt pathway agonist) were used to validate the mechanism of NGR1 on COPD. RESULTS: NGR1 inhibited the proliferation and migration, but caused cell cycle arrest for CSE-triggered ASMCs. Furthermore, NGR1 not only decreased IL-1ß, IL-6, IL-8, and TNF-α contents, but also reduced α-SMA expression in CSE-stimulated ASMCs. Moreover, NGR1restrainedTGF-ß1 expression, PI3K, p65, and AKT phosphorylation in CSE-stimulated ASMCs. Molecular docking experiments showed NGR1 exhibited a strong binding ability to PI3K, TGF-ß1, p65, and AKT. Notably, the effects of NGR1 on the proliferation and migration of CSE-induced ASMCs were reversed by 740 Y-P. CONCLUSIONS: NGR1 can restrain the proliferation and migration of CSE-induced ASMCs, indicating that NGR1 may be a therapeutic candidate for treating COPD.

Application of Residual Structure Time Convolutional Network Based on Attention Mechanism in Remaining Useful Life Interval Prediction of Bearings.

In the context of Industry 4.0, bearings, as critical components of machinery, play a vital role in ensuring operational reliability. The detection of their health status is thus of paramount importance. Existing predictive models often focus on point predictions of bearing lifespan, lacking the ability to quantify uncertainty and having room for improvement in accuracy. To accurately predict the long-term remaining useful life (RUL) of bearings, a novel time convolutional network model with an attention mechanism-based soft thresholding decision residual structure for quantifying the lifespan interval of bearings, namely TCN-AM-GPR, is proposed. Firstly, a spatio-temporal graph is constructed from the bearing sensor signals as the input to the prediction model. Secondly, a residual structure based on a soft threshold decision with a self-attention mechanism is established to further suppress noise in the collected bearing lifespan signals. Thirdly, the extracted features pass through an interval quantization layer to obtain the RUL and its confidence interval of the bearings. The proposed methodology has been verified using the PHM2012 bearing dataset, and the comparison of simulation experiment results shows that TCN-AM-GPR achieved the best point prediction evaluation index, with a 2.17% improvement in R2 compared to the second-best performance from TCN-GPR. At the same time, it also has the best interval prediction comprehensive evaluation index, with a relative decrease of 16.73% in MWP compared to the second-best performance from TCN-GPR. The research results indicate that TCN-AM-GPR can ensure the accuracy of point estimates, while having superior advantages and practical significance in describing prediction uncertainty.

Value delivery in green consumption: the effect of advertisement value proposition on consumer perception and purchase intention.

Amid the expanding green consumer market, companies are increasingly emphasizing their eco-friendly contributions in advertising. This study delves into the value delivery process within green consumption, guided by the service-dominant logic (S-D logic). A survey-based experiment with 589 responses reveals that the information frame in advertising significantly impacts consumer value perceptions and purchase intentions. Notably, the temporal frame of advertising plays a pivotal role, influencing consumers' value perceptions. Future framing enhances emotional value perceptions, while past framing promotes environmental value perceptions. This research enhances our understanding of value delivery mechanisms in green consumption and holds valuable implications for marketers of sustainable products.

Based on Network Pharmacology and Molecular Docking, the Active Components, Targets, and Mechanisms of Flemingia philippinensis in Improving Inflammation Were Excavated.

Flemingia philippinensis, a polyphenol-rich plant, holds potential for improving inflammation, but its mechanisms are not well understood. Therefore, this study employed network pharmacology and molecular docking to explore the mechanism by which Flemingia philippinensis ameliorates inflammation. In this study, 29 kinds of active ingredients were obtained via data mining. Five main active components were screened out for improving inflammation, which were flemichin D, naringenin, chrysophanol, genistein and orobol. In total, 52 core targets were identified, including AKT serine/threonine kinase 1 (AKT1), tumor necrosis factor (TNF), B-cell lymphoma-2 (BCL2), serum albumin (ALB), and estrogen receptor 1 (ESR1). Gene ontology (GO) enrichment analysis identified 2331 entries related to biological processes, 98 entries associated with cellular components, and 203 entries linked to molecular functions. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis yielded 149 pathways, including those involved in EGFR tyrosine kinase inhibitor resistance, endocrine resistance, and the PI3K-Akt signaling pathway. Molecular docking results showed strong binding effects between the main active components and the core targets, with binding energies less than -5 kcal/mol. In summary, this study preliminarily elucidated the underlying mechanisms by which Flemingia philippinensis, through a multi-component, multi-target, and multi-pathway approach, ameliorates inflammation. This provides a theoretical foundation for the subsequent application of Flemingia philippinensis in inflammation amelioration.

Uncovering the Role of Anoikis-Related Genes in Modulating Immune Infiltration and Pathogenesis of Diabetic Kidney Disease.

Background: Diabetic kidney disease (DKD) is an intricate complication of diabetes with limited treatment options. Anoikis, a programmed cell death activated by loss of cell anchorage to the extracellular matrix, participated in various physiological and pathological processes. Our study aimed to elucidate the role of anoikis-related genes in DKD pathogenesis. Methods: Differentially expressed genes (DEGs) associated with anoikis in DKD were identified. Weighted gene co-expression network analysis (WGCNA) was conducted to identify DKD-correlated modules and assess their functional implications. A diagnostic model for DKD was developed using LASSO regression and Gene set variation analysis (GSVA) was performed for enrichment analysis. Experimental validation was employed to validate the significance of selected genes in the progression of DKD. Results: We identified 10 anoikis-related DEGs involved in key signaling pathways impacting DKD progression. WGCNA highlighted the yellow module's significant enrichment in immune response and regulatory pathways. Correlation analysis further revealed the association between immune infiltration and anoikis-related DEGs. Our LASSO regression-based diagnostic model demonstrated a well-predictive efficacy with seven identified genes. GSVA indicated that gene function in the high-risk group was primarily associated with immune regulation. Further experimental validation using diabetic mouse models and data analysis in the single-cell dataset confirmed the significance of PYCARD and SFN in DKD progression. High glucose stimulation in RAW264.7 and TCMK-1 cells showed significantly increased expression levels of both Pycard and Sfn. Co-expression analysis demonstrated distinct functions of PYCARD and SFN, with KEGG pathway analysis showing significant enrichment in immune regulation and cell proliferation pathway. Conclusion: In conclusion, our study provides valuable insights into the molecular mechanisms involved in DKD pathogenesis, specifically highlighting the role of anoikis-related genes in modulating immune infiltration. These findings suggest that targeting these genes may hold promise for future diagnostic and therapeutic approaches in DKD management.

Prediction of cognitive decline in Parkinson's disease based on MRI radiomics and clinical features: A multicenter study.

OBJECTIVE: To develop and validate a multimodal combinatorial model based on whole-brain magnetic resonance imaging (MRI) radiomic features for predicting cognitive decline in patients with Parkinson's disease (PD). METHODS: This study included a total of 222 PD patients with normal baseline cognition, of whom 68 had cognitive impairment during a 4-year follow-up period. All patients underwent MRI scans, and radiomic features were extracted from the whole-brain MRI images of the training set, and dimensionality reduction was performed to construct a radiomics model. Subsequently, Screening predictive factors for cognitive decline from clinical features and then combining those with a radiomics model to construct a multimodal combinatorial model for predicting cognitive decline in PD patients. Evaluate the performance of the comprehensive model using the receiver-operating characteristic curve, confusion matrix, F1 score, and survival curve. In addition, the quantitative characteristics of diffusion tensor imaging (DTI) from corpus callosum were selected from 52 PD patients to further validate the clinical efficacy of the model. RESULTS: The multimodal combinatorial model has good classification performance, with areas under the curve of 0.842, 0.829, and 0.860 in the training, test, and validation sets, respectively. Significant differences were observed in the number of cognitive decline PD patients and corpus callosum-related DTI parameters between the low-risk and high-risk groups distinguished by the model (p < 0.05). The survival curve analysis showed a statistically significant difference in the progression time of mild cognitive impairment between the low-risk and the high-risk groups. CONCLUSIONS: The building of a multimodal combinatorial model based on radiomic features from MRI can predict cognitive decline in PD patients, thus providing adaptive strategies for clinical practice.

Chemoproteomics enables identification of coatomer subunit zeta-1 targeted by a small molecule for enterovirus A71 inhibition.

Human enterovirus A71 (EV-A71) is a significant etiological agent responsible for epidemics of hand, foot, and mouth disease (HFMD) in Asia-Pacific regions. There are presently no licensed antivirals against EV-A71, and the druggable target for EV-A71 remains very limited. The phenotypic hit 10,10'-bis(trifluoromethyl) marinopyrrole A derivative, herein termed MPA-CF3, is a novel potent small-molecule inhibitor against EV-A71, but its pharmacological target(s) and antiviral mechanisms are not defined. Here, quantitative chemoproteomics deciphered the antiviral target of MAP-CF3 as host factor coatomer subunit zeta-1 (COPZ1). Mechanistically, MPA-CF3 disrupts the interaction of COPZ1 with the EV-A71 nonstructural protein 2C by destabilizing COPZ1 upon binding. The destruction of this interaction blocks the coatomer-mediated transport of 2C to endoplasmic reticulum, and ultimately inhibits EV-A71 replication. Taken together, our study disclosed that MPA-CF3 can be a structurally novel host-targeting anti-EV-A71 agent, providing a structural basis for developing the COPZ1-targeting broad-spectrum antivirals against enteroviruses. The mechanistic elucidation of MPA-CF3 against EV-A71 may offer an alternative COPZ1-involved therapeutic pathway for enterovirus infection.

Maternal Serum Polyols and Its Link to Gestational Diabetes Mellitus: A Population-Based Nested Case-Control Study.

CONTEXT: Sugar alcohols (also called polyols) are regarded as a "healthy" sugar substitute. One of the possible reasons for their safe use in pregnant women is their natural origin and the presence of polyols in maternal and fetal samples during normal human gestation. But little is known about the association between circulating sugar alcohols levels and maternal metabolic disorders during pregnancy. OBJECTIVE: We aimed to detect the concentration of the polyols in participants with and without gestational diabetes mellitus (GDM), and to investigate the association between maternal serum levels of polyols and GDM, as well as newborn outcomes. METHODS: A nested population-based case-control study was conducted in 109 women with and without GDM. Maternal concentrations of serum erythritol, sorbitol, and xylitol in the fasting state were quantified using a time of flight mass spectrometry system. RESULT: In women with GDM, serum concentrations of erythritol and sorbitol were higher, but serum concentrations of xylitol were lower than those in women without GDM. Per 1-SD increment of Box-Cox-transformed concentrations of erythritol and sorbitol were associated with the increased odds of GDM by 43% and 155% (95% CI 1.07-1.92 and 95% CI 1.77-3.69), while decreased odds were found for xylitol by 25% (95% CI 0.57-1.00). Additionally, per 1-SD increase of Box-Cox-transformed concentrations of serum sorbitol was associated with a 52% increased odds of large for gestational age newborns controlling for possible confounders (95% CI 1.00-2.30). CONCLUSION: Maternal circulating sugar alcohols levels during pregnancy were significantly associated with GDM. These findings provide the potential roles of polyols on maternal metabolic health during pregnancy.

Luteinizing Hormone Receptor Mutation (LHRN316S) Causes Abnormal Follicular Development Revealed by Follicle Single-Cell Analysis and CRISPR/Cas9.

Abnormal interaction between granulosa cells and oocytes causes disordered development of ovarian follicles. However, the interactions between oocytes and cumulus granulosa cells (CGs), oocytes and mural granulosa cells (MGs), and CGs and MGs remain to be fully explored. Using single-cell RNA-sequencing (scRNA-seq), we determined the transcriptional profiles of oocytes, CGs and MGs in antral follicles. Analysis of scRNA-seq data revealed that CGs may regulate follicular development through the BMP15-KITL-KIT-PI3K-ARF6 pathway with elevated expression of luteinizing hormone receptor (LHR). Because internalization of the LHR is regulated by Arf6, we constructed LHRN316S mice by CRISPR/Cas9 to further explore mechanisms of follicular development and novel treatment strategies for female infertility. Ovaries of LHRN316S mice exhibited reduced numbers of corpora lutea and ovulation. The LHRN316S mice had a reduced rate of oocyte maturation in vitro and decreased serum progesterone levels. Mating LHRN316S female mice with ICR wild type male mice revealed that the infertility rate of LHRN316S mice was 21.4% (3/14). Litter sizes from LHRN316S mice were smaller than those from control wild type female mice. The oocytes from LHRN316S mice had an increased rate of maturation in vitro after progesterone administration in vitro. Furthermore, progesterone treated LHRN316S mice produced offspring numbers per litter equivalent to WT mice. These findings provide key insights into cellular interactions in ovarian follicles and provide important clues for infertility treatment.

Molecular mechanism of the NOS/NOX regulation of antibacterial activity in Eriocheir sinensis.

To elucidate the role of nitric oxide synthase (NOS), which produces the free radical nitric oxide (NO), and nicotinamide adenine dinucleotide phosphate oxidase (NOX), which produces the superoxide anion (O2-), in the innate immunity of Eriocheir sinensis, the full lengths of the NOS and NOX genes were cloned via rapid amplification of the cDNA ends and then expressed in the prokaryotic form to obtain the recombinant proteins, NOS-HIS and NOX-HIS. Through bacterial binding and stimulation experiments, the molecular mechanisms of NOS and NOX in the innate immunity of E. sinensis were explored. Based on the results, NOS and NOX were 5900 bp and 4504 bp long, respectively, and were evolutionarily conserved. Quantitative real-time PCR revealed that NOS and NOX were expressed in all studied tissues, and both were expressed in the highest amounts in hemocytes. NOS-HIS and NOX-HIS could bind to bacteria with different binding powers; their binding ability to gram-positive bacteria was higher than that of binding to gram-negative bacteria. After stimulation with Aeromonas hydrophila, NOS expression was significantly up-regulated at 3, 6, and 48 h, and NOX expression was significantly down-regulated at 3, 12, 24, and 48 h. After bacterial stimulation, the NOS enzyme activity in the serum of E. sinensis was also significantly up-regulated at 6 and 48 h, and the NOX enzyme activity was significantly down-regulated at 12 and 48 h, aligning with the gene expression trend. Moreover, the related free radical molecules, NO, O2-, and H2O2, tended to decrease after bacterial stimulation. Overall, the gene expression and enzyme activity of NOS and NOX had been changed respectively, and the contents of a series of free radical molecules (NO, O2- and H2O2) were induced in E. sinensis after bacterial stimulation, which then exert antibacterial immunity.

Unveiling FOS as a Potential Diagnostic Biomarker and Emetine as a Prospective Therapeutic Agent for Diabetic Nephropathy.

Background: Diabetic nephropathy (DN) is one of the primary causes of end-stage renal disease, yet effective therapeutic targets remain elusive. This study aims to identify novel diagnostic biomarkers and potential therapeutic candidates for DN. Methods: Differentially expressed genes (DEGs) in GSE96804 and GSE142025 were identified and functional enrichment analysis was performed. Diagnostic biomarkers were selected using machine learning algorithms and evaluated by Receiver Operating Characteristic analysis. c-Fos expression was validated in an established DN mouse model. Immune infiltration levels were assessed with Single-Sample Gene Set Enrichment Analysis. Co-expression analysis revealed regulatory relationships involving FOS. cMAP predicted potential therapeutic candidates. Transcriptome sequencing and experiments in RAW264.7 cells was performed to investigate molecular mechanisms of emetine. Results: In both datasets, we identified 44 upregulated and 74 downregulated DEGs involved in focal adhesion, ECM-receptor interaction, and the PI3K-Akt signaling pathway. FOS emerged as a robust diagnostic marker with decreased expression in DN patients and DN mouse. Co-expression analysis revealed potential regulatory mechanisms of FOS, implicating the MAPK signaling pathway, regulation of cell proliferation and apoptotic signaling pathways. Immune dysregulation was observed in DN patients. Notably, emetine was identified as a potential therapeutic candidate. Transcriptome sequencing and experimental validation demonstrated emetine suppressed M1 macrophage polarization by inhibiting the activation of NF-κB signaling pathway, as well as reducing the expression of Il-18 and Ccl5. Conclusion: In conclusion, our study identified FOS as a promising diagnostic biomarker and emetine as a potential therapeutic candidate for DN. These findings enhance our understanding of DN pathogenesis and present novel prospects for therapeutic strategies.