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Bank erosion is a key feature of channel evolution in alluvial rivers, and will occur under the combined effect of hydraulic erosion and frost heave/freeze-thaw process of rivers in seasonal frozen regions. However, most research on bank erosion modeling has seldom considered the impact of the frost heave/freeze-thaw process. Therefore, the variation in the mechanical characteristics of riverbank soil under the freeze-thaw cycle was investigated firstly in the current research and then used in the modeling of bank erosion processes at typical sections of the Songhua River. Additionally, a sensitivity analysis of riverbank stability was conducted using orthogonal experiments. The results indicate that after 7 freeze-thaw cycles, the soil cohesion and internal friction angle of bank soil decreased by about 10%–47 % and 9%–19 %, respectively. Unlike lowland rivers, bank erosion of rivers in seasonal frozen regions is more likely to occur during the rising water period. The frost heaving/freeze-thaw process will make the bank stability safety coefficient Fs more quickly decrease to the unstable critical value. As compared with the case without considering the frost heaving/freeze-thaw process, the mass failure occurred in advance when the frost heaving/freeze-thaw process was considered, and the calculated bank erosion volume was increased by 11%–51 %, agreeing better with the measured value. The sensitivity ranking of the four influencing factors on riverbank stability under freezing-thawing conditions is as follows: river stage > groundwater level > cohesion > internal friction angle. The current study can provide a reference for research on bank erosion and channel evolution of rivers in seasonal frozen regions.

Summary: Energy crops play a vital role in meeting future energy and chemical demands while addressing climate change. However, the idealization of low-carbon workflows and careful consideration of cost-benefit equations are crucial for their more sustainable implementation. Here, we propose tobacco as a promising energy crop because of its exceptional water solubility, mainly attributed to a high proportion of water-soluble carbohydrates and nitrogen, less lignocellulose, and the presence of acids. We then designed a strategy that maximizes biomass conversion into bio-based products while minimizing energy and material inputs. By autoclaving tobacco leaves in water, we obtained a nutrient-rich medium capable of supporting the growth of microorganisms and the production of bioproducts without the need for extensive pretreatment, hydrolysis, or additional supplements. Additionally, cultivating tobacco on barren lands can generate sufficient biomass to produce approximately 573 billion gallons of ethanol per year. This approach also leads to a reduction of greenhouse gas emissions by approximately 76% compared to traditional corn stover during biorefinery processes. Therefore, our study presents a novel and direct strategy that could significantly contribute to the goal of reducing carbon emissions and global sustainable development compared to traditional methods.

Accurate calculation of flow discharge for sluice gates is essential in irrigation, water supply, and structure safety. The measurement of discharge with the requirement of distinguishing flow regimes is not conducive to application. In this study, a novel approach that considers both free and submerged flow was proposed. The energy–momentum method was employed to derive the coefficient of discharge. Subsequently, the discharge coefficient was determined through the experiment which was performed on the physical model of a vertical sluice gate with a broad-crested weir. Feature engineering, incorporating dimensional analysis, feature construction, and correlation-based selection were performed. The best subset regression method was employed to develop regression equations of the discharge coefficient with the generated features. The derived formula was applied to compute the discharge coefficient in the vertical sluice gate and determine the flow discharge. The accuracy of adopted method was assessed by comparing it with recent studies on submerged flow, and the results demonstrate that the developed approach achieves a high level of accuracy in calculating flow discharge. The coefficient of determination for the calculated flow rate is 0.993, and the root mean square percentage error is 5.04%. HIGHLIGHTS The feature combination with efficient interpretability of free-submerged flow discharge coefficient was proposed.; The computational equation applicable to free-submerged flow regimes based on the EM method was established with high accuracy.; The process of feature selection and calculation is not complicated and has potential for automated calibration.;

For many applications, raw satellite observations need to be converted to high-level products of various essential environmental variables. While numerous products are available at kilometer spatial resolutions, there are few global products at high spatial resolutions (10–30 m), which are also referred to fine or medium resolutions in the literature. To facilitate the development of more high spatial resolution products, this paper systematically reviews the state-of-the-art progress on inversion algorithms and publicly available regional and global products. We begin with an inventory of available high-resolution satellite data, and then present different algorithms for determining cloud masks, estimating aerosol optical depth, and performing atmospheric correction and topographic correction for land surface reflectance retrieval. The majority of this paper reviews the inversion algorithms and existing regional to global products of 18 variables in four major categories: 1) Land surface radiation, including broadband albedo, land surface temperature, and all-wave net radiation; 2) Terrestrial ecosystem variables, including leaf area index, fraction of absorbed photosynthetically active radiation, fractional vegetation cover, fractional forest cover, tree height, forest above-ground biomass gross primary production, net primary production, and agricultural crop yield; 3) Water cycle and cryosphere, including soil moisture, evapotranspiration, and snow cover; and 4) Land surface types, such as global land cover, impervious surface, inland water, crop type, and fire. Since the existing products over large regions are usually spatially discontinuous due to cloud contamination, different data fusion and data assimilation algorithms and some products for producing spatially seamless and temporally continuous products are presented. In the end, we discuss a variety of challenges in generating global high spatial resolution satellite products.

Mutations in CHCHD2 have been reported to be associated with familial Parkinson’s disease (PD). We generated a human induced pluripotent stem cell (hiPSC) line by reprogramming dermal fibroblasts from a PD patient harboring a novel CHCHD2 mutation (c.434G > A, p.R145Q). This line exhibited human embryonic stem cell (hESC)-like clonal morphology, expression of undifferentiated stem cell markers, a normal karyotype and trilineage differentiation capacity and thus the potential to serve as a model for further investigating the underlying molecular mechanisms of CHCHD2 function in PD.

Summary: Background: Hepatocellular carcinoma (HCC) is a highly prevalent and deadly type of cancer, and although pharmacotherapy remains the cornerstone of treatment, therapeutic outcomes are often unsatisfactory. Pharmacological inhibition of mammalian target of rapamycin (mTOR) has been closely associated with HCC regression. Methods: Herein, we covalently conjugated AZD8055, a potent mTORC1/2 blocker, with a small panel of unsaturated fatty acids via a dynamically activating linkage to enable aqueous self-assembly of prodrug conjugates to form mTOR nanoblockers. Cell-based experiments were carried out to evaluate the effects of the nanoblocker against hepatocellular carcinoma (HCC) cells. The orthotopic and subcutaneous HCC mouse models were established to examine its antitumour activity. Findings: Among several fatty acids as promoieties, linoleic acid-conjugated self-assembling nanoblocker exhibited optimal size distribution and superior physiochemical properties. Compared with free agents, PEGylated AZD8055 nanoblocker (termed AZD NB) was pharmacokinetically optimized after intravenous administration. In vivo investigations confirmed that AZD NB significantly suppressed tumour outgrowth in subcutaneous HCCLM3 xenograft, Hepatoma-22, and orthotopic Hepa1-6 liver tumour models. Strikingly, treatment with AZD NB, but not free agent, increased intratumour infiltration of IFN-γ+CD8+ T cells and CD8+ memory T cells, suggesting a potential role of the mTOR nanoblocker to remodel the tumour microenvironment. Overall, a single conjugation with fatty acid transformed a hydrophobic mTOR blocker into a systemically injectable nanomedicine, representing a facile and generalizable strategy for improving the therapeutic index of mTOR inhibition-based cancer therapy. Interpretation: The mTOR inhibition by chemically engineered nanoblocker presented here had enhanced efficacy against tumours compared with the pristine drug and thus has the potential to improve the survival outcomes of patients with HCC. Additionally, this new nanosystem derived from co-assembling of small-molecule prodrug entities can serve as a delivery platform for the synergistic co-administration of distinct pharmaceutical agents. Funding: This work was supported by the National Natural Science Foundation of China (32171368,81721091), the Zhejiang Provincial Natural Science Foundation of China (LZ21H180001), the Jinan Provincial Laboratory Research Project of Microecological Biomedicine (JNL-2022039c and JNL-2022010B), State Key Laboratory for Diagnosis and Treatment of Infectious Diseases (zz202310), and Natural Science Foundation of Shandong Province (ZR2023ZD59).

Retinal degeneration (RD) is a group of chronic blinding diseases characterised by progressive retinal cell death. As the disease progresses, vision deteriorates due to retinal cell death and impaired retinal integrity, eventually leading to complete loss of vision. Therefore, the function and environmental homeostasis of the retina have an important impact on the pathogenesis and treatment of RD. Ubiquitination, as a complex post-translational modification process, plays an essential role in maintaining retinal homeostasis and normal function. It covalently combines ubiquitin with protein through a series of enzyme-mediated reactions, and participates in cell processes such as gene transcription, cell cycle process, DNA repair, apoptosis and immune response. At the same time, it plays a central role in protein degradation. There are two major protein degradation systems in eukaryotic cells: the ubiquitin-proteasome system and the autophagy-lysosomal system. The protein degradation pathway maintains retinal protein homeostasis by reducing abnormal protein accumulation in the retina through two modes of degradation. Either dysregulation of ubiquitination or disruption of protein homeostasis may lead to the development of RD. This article aims to comprehensively review recent research progress on ubiquitin-related genes, proteins and protein homeostasis in the pathogenesis of RD, and to summarize the potential targeted therapy strategies for it. The review is expected to provide valuable guidance for further development and application of ubiquitination in RD.

The technology of Blockchain has the characteristics of decentralization, non-tampering and traceability, and it is applied to the traceability of green food, it helps to solve the quality and safety problems of Information asymmetry and untrustworthy green food. However, with the development of the network and complexity of the green food supply chain, more and more traceability information is needed. In this paper, the blockchain side chain is introduced to build a credible platform for the traceability of green food with multi-chain on the main chain. The main chain is enlarged by the side chain to improve its storage capacity, and the Bloom filter modified Bmerkle tree is used to improve the efficiency of traceability queries. Finally, the running process of traceability platform is analyzed by taking specific green food as an example. The construction of trusted main-side multi-chain traceability platform can eliminate the Information asymmetry in complex supply chain network, ensure the authenticity of traceability information, and enhance consumer confidence in green food. At the same time, it can expand the storage capacity of single chain, improve the efficiency of traceability query and protect the privacy of private data. And it is hoped to provide reference for the application of block chain technology in traceability system.

Abstract The often immune-suppressive tumor microenvironment (TME) may hinder immune evasion and response to checkpoint blockade therapies. Pharmacological activation of the STING pathway does create an immunologically hot TME, however, systemic delivery might lead to undesired off-target inflammatory responses. Here, we generate a small panel of esterase-activatable pro-drugs based on the structure of the non-nucleotide STING agonist MSA-2 that are subsequently stably incorporated into a liposomal vesicle for intravenous administration. The pharmacokinetic properties and immune stimulatory capacity of pro-drugs delivered via liposomes (SAProsomes) are enhanced compared to the free drug form. By performing efficacy screening among the SAProsomes incorporating different pro-drugs in syngeneic mouse tumor models, we find that superior therapeutic performance relies on improved delivery to the desired tumor and lymphoid compartments. The best candidate, SAProsome-3, highly stimulates secretion of inflammatory cytokines and creates a tumoricidal immune landscape. Notably, upon application to breast cancer or melanoma mouse models, SAProsome-3 elicits durable remission of established tumors and postsurgical tumor-free survival while decreasing metastatic burden without significant systemic toxicity. In summary, our work establishes the proof of principle for a better targeted and more efficient and safe STING agonist therapy.

Abstract Temperature is the most concerned factor in the human–environment interactions. Apparent temperature accounting for other meteorological variables, such as humidity, wind speed and solar radiation, is the equivalent temperature, and it is a more accurate indicator to reflect human's environmental temperature perception. High‐quality apparent temperature data are urgently needed for the further research on human–environment interactions. At the same time, as global heat waves continue to increase in frequency, duration and intensity, understanding the impact of heat waves on human health needs human perception‐based heat wave data. Using ERA5 hourly data on single levels of 2 m temperature, wind speed, dewpoint temperature and solar radiation, this study developed a global apparent temperature and heat wave (GATHW) toolbox based on the Climate Data Store (CDS) online platform. This toolbox allows using three methods to calculate daily apparent temperature and heat wave at three spatial resolutions of 0.25°, 0.5° and 1° respectively. It can realize online calculation, display and real‐time download and is updated in near real‐time. The global daily apparent temperature and annual heat wave dataset from 2006 to 2020 calculated by the toolbox can be obtained from https://www.doi.org/10.5281/zenodo.4764325. After evaluation, this dataset can well reflect the typical extreme temperatures and heat wave events, and is more accurate, with higher resolution and faster update frequency than similar data products, which can provide data support for the study of human–environmental interactions and extreme climate events.

Abstract Immunotherapy has recently emerged as the predominant therapeutic approach for cervical cancer (CCa), driven by the groundbreaking clinical achievements of immune checkpoint inhibitors (ICIs), such as anti‐PD‐1/PD‐L1 antibodies. N4‐acetylcytidine (ac4C) modification, catalyzed by NAT10, is an important posttranscriptional modification of mRNA in cancers. However, its impact on immunological dysregulation and the tumor immunotherapy response in CCa remains enigmatic. Here, a significant increase in NAT10 expression in CCa tissues is initially observed that is clinically associated with poor prognosis. Subsequently, it is found that HOXC8 activated NAT10 by binding to its promoter, thereby stimulating ac4C modification of FOXP1 mRNA and enhancing its translation efficiency, eventually leading to induction of GLUT4 and KHK expression. Moreover, NAT10/ac4C/FOXP1 axis activity resulted in increased glycolysis and a continuous increase in lactic acid secretion by CCa cells. The lactic acid‐enriched tumor microenvironment (TME) further contributed to amplifying the immunosuppressive properties of tumor‐infiltrating regulatory T cells (Tregs). Impressively, NAT10 knockdown enhanced the efficacy of PD‐L1 blockade‐mediated tumor regression in vivo. Taken together, the findings revealed the oncogenic role of NAT10 in initiating crosstalk between cancer cell glycolysis and immunosuppression, which can be a target for synergistic PD‐1/PD‐L1 blockade immunotherapy in CCa.

Abstract Precipitation is an important component of the hydrological cycle and has significant impact on ecological environment and social development, especially in arid areas where water resources are scarce. As a typical arid and semi-arid region, the Mongolian Plateau is ecologically fragile and highly sensitive to climate change. Reliable global precipitation data is urgently needed for the sustainable development over this gauge-deficient region. With high-quality estimates, fine spatiotemporal resolutions, and wide coverage, the state-of-the-art Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) and European Center for Medium-range Weather Forecasts Reanalysis 5 (ERA5) have great potential for regional climatic, hydrological, and ecological applications. However, how they perform has not been well investigated on the Mongolian Plateau. Therefore, this study evaluated the performance of three IMERG V06 datasets (ER, LR and FR), two ERA5 products (ERA5-HRES and ERA5-Land), and their predecessors (TMPA-3B42 and ERA-Interim) over the region across 2001–2018. The results showed that all products broadly characterized seasonal precipitation cycles and spatial patterns, but only the three reanalysis products, IMERG FR and TMPA-3B42 could capture interannual and decadal variability. When describing daily precipitation, dataset performances ranked ERA5-Land > ERA5-HRES > ERA-Interim > IMERG FR > IMERG LR > IMERG ER > TMPA-3B42. All products showed deficiencies in overestimating weak precipitation and underestimating high-intensity precipitation. Besides, products performed best in agricultural lands and forests along the northern and south-eastern edges, followed by urban areas and grasslands closer to the center, and worst in the sparse vegetation and bare areas of the south-west. Due to a negative effect of topographic complexity, IMERG showed poor detection capabilities in forests. Accordingly, this research currently supports the applicability of reanalysis ERA5 data over the arid, topographically complex Mongolian Plateau, which can inform regional applications with different requirements.

Abstract Immune checkpoint blockade (ICB) therapies have had a tremendous impact on cancer therapy. However, most patients harbor a poorly immunogenic tumor microenvironment (TME), presenting overwhelming de novo refractoriness to ICB inhibitors. To address these challenges, combinatorial regimens that employ chemotherapies and immunostimulatory agents are urgently needed. Here, a combination chemoimmunotherapeutic nanosystem consisting of a polymeric monoconjugated gemcitabine (GEM) prodrug nanoparticle decorated with an anti‐programmed cell death‐ligand 1 (PD‐L1) antibody (αPD‐L1) on the surface and a stimulator of interferon genes (STING) agonist encapsulated inside is developed. Treatment with GEM nanoparticles upregulates PD‐L1 expression in ICB‐refractory tumors, resulting in augmented intratumor drug delivery in vivo and synergistic antitumor efficacy via activation of intratumor CD8+ T cell responses. Integration of a STING agonist into the αPD‐L1‐decorated GEM nanoparticles further improves response rates by transforming low‐immunogenic tumors into inflamed tumors. Systemically administered triple‐combination nanovesicles induce robust antitumor immunity, resulting in durable regression of established large tumors and a reduction in the metastatic burden, coincident with immunological memory against tumor rechallenge in multiple murine tumor models. These findings provide a design rationale for synchronizing STING agonists, PD‐L1 antibodies, and chemotherapeutic prodrugs to generate a chemoimmunotherapeutic effect in treating ICB‐nonresponsive tumors.

Skeletal muscle stem cells (also known as satellite cells [SCs]) are essential for muscle regeneration and the regenerative activities of SCs are intrinsically governed by gene regulatory mechanisms, but the post-transcriptional regulation in SCs remains largely unknown. N(6)-methyladenosine (m6A) modification of RNAs is the most pervasive and highly conserved RNA modification in eukaryotic cells; it exerts powerful impact on almost all aspects of mRNA processing that is mainly endowed by its binding with m6A reader proteins. In this study, we investigate the previously uncharacterized regulatory roles of YTHDC1, an m6A reader in mouse SCs. Our results demonstrate that YTHDC1 is an essential regulator of SC activation and proliferation upon acute injury-induced muscle regeneration. The induction of YTHDC1 is indispensable for SC activation and proliferation; thus, inducible YTHDC1 depletion almost abolishes SC regenerative capacity. Mechanistically, transcriptome-wide profiling using LACE-seq in both SCs and mouse C2C12 myoblasts identifies m6A-mediated binding targets of YTHDC1. Next, splicing analysis defines splicing mRNA targets of m6A-YTHDC1. Furthermore, nuclear export analysis also leads to the identification of potential mRNA export targets of m6A-YTHDC1 in SCs and C2C12 myoblasts;interestingly, some mRNAs can be regulated at both splicing and export levels. Lastly, we map YTHDC1 interacting protein partners in myoblasts and unveil a myriad of factors governing mRNA splicing, nuclear export, and transcription, among which hnRNPG appears to be a bona fide interacting partner of YTHDC1. Altogether, our findings uncover YTHDC1 as an essential factor controlling SC regenerative ability through multifaceted gene regulatory mechanisms in mouse myoblast cells.

Objectives The purpose of this study was to use easily obtained and directly observable clinical features to establish predictive models to identify patients at increased risk of stroke.Setting and participants A total of 46 240 valid records were obtained from 8 research centres and 14 communities in Jiangxi province, China, between February and September 2018.Primary and secondary outcome measures The area under the receiver operating characteristic curve (AUC), sensitivity, specificity and accuracy were calculated to test the performance of the five models (logistic regression (LR), random forest (RF), decision tree (DT), extreme gradient boosting (XGBoost) and gradient boosting DT). The calibration curve was used to show calibration performance.Results The results indicated that XGBoost (AUC: 0.924, accuracy: 0.873, sensitivity: 0.776, specificity: 0.916) and RF (AUC: 0.924, accuracy: 0.872, sensitivity: 0.778, specificity: 0.913) demonstrated excellent performance in predicting stroke. Physical inactivity, hypertension, meat-based diet and high salt intake were important prediction features of stroke.Conclusion The five machine learning models all had good predictive and discriminatory performance for stroke. The performance of RF and XGBoost was slightly better than that of LR, which was easier to interpret and less prone to overfitting. This work provides a rapid and accurate tool for stroke risk assessment, which can help to improve the efficiency of stroke screening medical services and the management of high-risk groups.

Gross primary productivity (GPP) over the Mongolian Plateau (MP) is a vital component of the global terrestrial carbon cycle. Using the latest MODIS GPP estimates at the best achievable spatial resolution along with several ancillary datasets, we investigated GPP variations in the MP region during 2001–2018 and attributed these changes to land-surface temperature ( $T_{\mathrm {s}}$ ), total precipitation ( $P_{\mathrm {t}}$ ), land-cover change (LCC), and atmospheric carbon dioxide (CO2) concentrations. The 18-year-averaged annual cumulative GPP in the MP region was 357.02 ± 24.76 gC $\text{m}^{-2}$ yr−1 during the study period, ranging from 60.51 ± 6.10 gC m−2 yr−1 in deserts to 596.41 ± 35.49 gC m−2 yr−1 in forests. A linear regression analysis indicated a significant overall increase in GPP, at a rate of 3.91 gC m−2 yr−1 ( $p < 0.01$ ). In comparison, GPP increased at a rate of 0.79 gC m−2 yr−1 in deserts ( $p < 0.01$ ), 4.79 gC m−2 yr−1 in forests ( $p < 0.01$ ), and 5.76 gC m−2 yr−1 in grasslands ( $p < 0.01$ ). Our detailed attribution analysis indicates that GPP is positively sensitive to surface air temperature (0.15 gC °C−1) and total precipitation (0.25 gC mm−1) but negatively sensitive to atmospheric CO2 concentrations (−0.20 gC mol−1) and LCC (−0.93 gC class−1). Furthermore, we reported large differences in the spatial patterns and magnitudes among individual variables in the GPP attribution analysis, with LCC proving to be the dominant factor followed by CO2 fertilization effects; climatic factors had comparatively little influence on GPP variations during the study period. Although MODIS GPP does not take CO2 fertilization effect into account, the close relationship between MODIS GPP and atmospheric CO2 concentrations still pose referencing value in attributing the GPP increase in this period. Overall, the findings of this study contribute to our understanding of the responses of sensitive ecosystems to the competing effects of climate change and human disturbance at regional scales.

Advances in snow-cover mapping techniques have resulted in more accurate estimation of fractional snow cover (FSC) in areas with no vegetation; however, vegetation interference limits the accuracy of available snow cover information from satellite observations. The aim of this study was to develop a robust and enhanced FSC-retrieval algorithm using Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data for vegetated areas. The experiments were conducted in North America, where vegetation cover is complex and heterogeneous, using 28 Landsat-8 – MODIS image pairs acquired for the entire snow cover season (September 2015–May 2016). The FSC retrieval models were established from 20 sub-models based on the Extremely Randomized Trees method incorporating input information from multiple sources, such as commonly used variables, vegetation- and snow-related variables, location and geometry related variables, and other auxiliary variables. The FSC retrieval models were divided into forest- and non-forest types. We further investigated a canopy correction method to mitigate vegetation interference effects caused by the viewing geometry of satellite observations. The results show that the integration of 20 sub-models largely decreased model dependence on the training sample quality and improved the robustness of the model predictions. In the validation of the independent dataset, there was a noticeable improvement in FSC estimation for different land-cover and vegetation-cover types, with root-mean-square errors (RMSEs) reduced by an average of 11% compared to the Trimmed-Model. The application of canopy correction under the “Recommend” conditions (i.e., viewing zenith angle in [45°,70°] and fraction of forest cover in [0,0.3]) improved the FSC prediction accuracy. Moreover, based on a comparison with the MOD10A1-based FSC map, our FSC estimation showed improved consistency across various vegetation coverages based on the Landsat reference FSC values, with 40% lower RMSEs and 8% increase in overall accuracy.

Skeletal muscle stem cells (or satellite cells, SCs) are normally quiescent but activate and expand in response to injury. Here the authors show that induction of DHX36 helicase during SC activation promotes mRNA translation by binding to 5′UTR mRNA G-quadruplexes (rG4) in targets including Gnai2 and unwinding them.

Balance rehabilitation is exceedingly crucial during stroke rehabilitation and is highly related to the stroke patients’ secondary injuries (caused by falling). Stroke patients focus on walking ability rehabilitation during the early stage. Ankle dorsiflexion can activate the brain areas of stroke patients, similar to walking. The combination of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) was a new method, providing more beneficial information. We extracted the event-related desynchronization (ERD), oxygenated hemoglobin (HBO), and Phase Synchronization Index (PSI) features during ankle dorsiflexion from EEG and fNIRS. Moreover, we established a linear regression model to predict Berg Balance Scale (BBS) values and used an eightfold cross validation to test the model. The results showed that ERD, HBO, PSI, and age were critical biomarkers in predicting BBS. ERD and HBO during ankle dorsiflexion and age were promising biomarkers for stroke motor recovery.

IntroductionSmall for gestational age (SGA) infants are at a higher risk of neurodevelopmental delay than infants appropriate for gestational age (AGA). Previous studies have confirmed that gut microbiota in early life influences subsequent neurodevelopment. However, few studies have reported corresponding data in SGA populations.ObjectiveWe aimed to evaluate the characteristics of the gut microbiota of term SGA infants and the associations between the gut microbiota in SGA infants and neurodevelopmental outcomes at 6 months of age.MethodsFecal samples were collected on days 1, 3, 5, and 7 from term SGA and AGA infants born between June 2020 and June 2021 at the Peking University First Hospital. 16S ribosomal deoxyribonucleic acid amplicon sequencing was used to analyze the fecal microbiota. We followed up for 6 months and used the Ages and Stages Questionnaires-3 (ASQ-3) to evaluate the neurodevelopmental outcomes among SGA infants.ResultsA total of 162 neonates were enrolled, with 41 SGA infants (25.3%) in the study group and 121 AGA infants (74.7%) in the control group. The gut microbial diversity in the SGA group was lower than that in the AGA group on days 1, 3, 5, and 7. Non-metric multidimensional scaling and analysis of similarities showed significant differences between the two groups. The SGA group had increased relative abundances of Ralstonia (3, 5, and 7 days) and Clostridium (3 and 7 days). The dominant microorganisms of the SGA group were Ralstonia on day 1, Escherichia_Shigella on days 3 and 7, and Clostridia on day 5. We found that the gut microbial diversity of SGA infants with poor communication scores was higher than that of SGA infants with good communication scores on day 3. Fine motor scores were negatively correlated with the relative abundance of Bacteroides_fragilis on day 1. A negative correlation was observed between gross motor scores and relative abundance of Clostridium_saccharobutylicum on day 7. Bacteroidota, Bacteroidia, Bacteroides, and Bacteroides_fragilis were the dominant microorganisms in the good communication score group on day 7. Communication scores were positively correlated with the relative abundance of Bacteroidota, Bacteroides, and Bacteroides_fragilis on day 7.ConclusionThe gut microbial diversity of term SGA infants was significantly lower in the first week of life than that of term AGA infants. Certain pathogenic and conditional pathogenic bacteria, such as Escherichia_Shigella, Ralstonia and Clostridium increased or formed the dominant microbiota in SGA infants. Alpha diversity, Bacteroidota, Bacteroides, Bacteroides_fragilis, and Clostridium_saccharobutylicum found in SGA infants may be associated with neurodevelopmental outcomes at 6 months of age, indicating possible therapeutic targets for clinical intervention.

AimsTo reveal the impact of eleven risk factors on stroke and provide estimates of the prevention potential.MethodsWe completed a multicenter case-control study in Jiangxi, China, a middle-income area. Neuroimaging examination was performed in all cases. Controls were stroke-free adults recruited from the community in the case concentration area. Conditional logistic regression and unconditional logistic regression were used for subgroup analysis of stroke type, and other groups (sex, age and urban-rural area), respectively. Odds ratios (ORs) and their population attributable risks (PARs) were calculated, with 95% confidence intervals.ResultsA total of 43,615 participants (11,735 cases and 31,880 controls) were recruited from February to September 2018, of whom we enrolled 11,729 case-control pairs. Physical inactivity [PAR 69.5% (66.9–71.9%)] and hypertension [53.4% (49.8–56.8%)] were two major risk factors for stroke, followed by high salt intake [23.9% (20.5–27.3%)], dyslipidemia [20.5% (17.1–24.0%)], meat-based diet [17.5% (14.9–20.4%)], diabetes [7.7% (5.9–9.7%)], cardiac causes [5.3% (4.0–6.7%)], alcohol intake [4.7% (0.2–10.0%)], and high homocysteine [4.3% (1.4–7.4%)]. Nine of these factors were associated with ischemic stroke, and five were associated with intracerebral hemorrhage. Collectively, eleven risk factors accounted for 59.9% of the PAR for all stroke (ischemic stroke: 61.0%; intracerebral hemorrhage: 46.5%), and were consistent across sex (men: 65.5%; women: 62.3%), age (≤55: 65.2%; >55: 63.5%), and urban-rural areas (city: 62.2%; county: 65.7%).ConclusionThe 11 risk factors associated with stroke identified will provide an important reference for evidence-based planning for stroke prevention in middle-income areas. There is an urgent need to improve awareness, management and control of behavioral and metabolic risk factors, particularly to promote physical activity and reduce blood pressure.

Due to the extremely high porosity and extremely low density of nano-porous thermal insulation materials, the characteristic size of the pores inside the materials and the characteristic size of the solid skeleton structure are on the nanometer scale, which leads to the obvious nanoscale effect of the heat transfer law inside the aerogel materials. Therefore, the nanoscale heat transfer characteristics inside the aerogel materials and the existing mathematical models for calculating the thermal conductivity of various heat transfer modes at the nanoscale need to be summarized in detail. Moreover, in order to verify the accuracy of the thermal conductivity calculation model of aerogel nano-porous materials, correct experimental data are required to modify the model. Because the medium is involved in radiation heat transfer, the existing test methods have a large error, which brings great difficulties to the design of nano-porous materials. In this paper, the heat transfer mechanism, characterization methods, and test methods of thermal conductivity of nano-porous materials are summarized and discussed. The main contents of this review are as follows. The first part introduces the structural characteristics and specific application environment of aerogel. In the second part, the characteristics of nanoscale heat transfer of aerogel insulation materials are analyzed. In the third part, the characterization methods of thermal conductivity of aerogel insulation materials are summarized. In the fourth part, the test methods of thermal conductivity of aerogel insulation materials are summarized. The fifth part gives a brief conclusion and prospect.

Abstract Background To validate markers for cervical carcinoma (CC) and precancerous lesions related with HPV infections. Methods Three different cervical cancer cell lines C-33A, SiHa and Caski were used for secretome profiling by label-free quantitative proteomics. Cervical exfoliated cells and matching serum samples were collected from 284 patients with normal control (n = 75, 26.41 %), precancerous lesions (n = 88, 30.99 %) and early stage cervical squamous carcinoma (n = 121, 42.61 %). HPV subtyping and quantification was performed by PCR and hybridization. 20 candidate proteins identified in previous screening studies (tissue, plasma, cells) were quantified by ELISA. Finally, highly quantitative parallel reaction monitoring mass spectrometry was used to assess the specificities and sensitivities of candidate serum markers. Results While CC was found to be associated with high-risk HPV subtypes, serum antibodies for high risk HPV were not significantly related to the progression of cervical cancer. Significant differences between patient groups were detected for the four proteins CLU, APOA4, APOE and MLH3, but none would allow clinical application due to insufficient sensitivity and specificity and large variability. Subsequent proteomic secretome analysis of cervical cancer cell lines identified a set of 729 common proteins. Cross referencing this dataset with ELISA measurements revealed six candidate proteins of which two, FBLN1 and ANT3, showed co-occurrence with HPV infection (75.7 % and 85 %, respectively) and had promising diagnostic ability in terms of sensitivity and specificity. After the loss of E6/E7 by using CRISPR/Cas9 gene editing, the content of ANT3 and FBLN1 in KoE6/E7 SiHa were downregulated, which indicated the expression of ANT3 and FBLN1 in cervical cancer may be affected by HPV infection. Conclusions FBLN1 and ANT3 might be potential tumor- and HPV-associated serum markers.

Chemotherapy is a critical treatment for endocrine-related cancers; however, chemoresistance and disease recurrence remain a challenge. The interplay between cancer cells and the tumor microenvironment via cell adhesion molecules (CAMs) promotes drug resistance, known as cell adhesion-mediated drug resistance (CAM-DR). CAMs are cell surface molecules that facilitate cell-to-cell or cell-to-extracellular matrix binding. CAMs exert an adhesion effect and trigger intracellular signaling that regulates cancer cell stemness maintenance, survival, proliferation, metastasis, epithelial–mesenchymal transition, and drug resistance. To understand these mechanisms, this review focuses on the role of CD44, cadherins, selectins, and integrins in CAM-DR in endocrine-related cancers.

Long noncoding RNA SAM (Sugt1 associated muscle) is upregulated in the proliferating myoblast cells. Here the authors investigate SAM knockout mice and suggest that SAM binds and stabilizes Sugt1, a co-chaperone protein that regulates kinetochore assembly.

There are significant differences between crude oil properties and enrichment horizon across the Gaoliu Fault in the Gaoshangpu area of the Nanpu Sag.Oils are mainly enriched in the third member of Shahejie Formation (Es3) to the north of the Gaoliu Fault, and are characterized by a high wax content.However, oils are mainly enriched in the Minghuazhen, Guantao and Dongying formations to the south of the Gaoliu Fault, and are normal crude oils with a low wax content. The biomarkers and compound specific isotopes of crude oils from different layers show that the origin of the high wax content oils in the Es3 is different from that of the oils to the south of the Gaoliu Fault. The former is derived from the source rocks of the Es34 and the latter is sourced from the third member of the Dongying Formation (Ed3) in the Linque Sub-Sag to the south of the Gaoliu Fault. The source rocks of the Es34 contain abundant terrigenous higher plants and lower hydrobionts, which provide the wax source. The microbe reformation, low thermal evolution degree and abnormal high pressure in the Es3 are key factors in the formation, migration and preservation of high wax oils.

Heat waves are continuous high temperature processes, which are defined as the daily maximum temperature exceeding the absolute-relative combined high temperature thresholds for more than three consecutive days in this study. Because of its unprecedented casualties, devastating compound disasters and irreversible deterioration trends, heat waves have attracted worldwide concern, while its global changes and socioeconomic impacts still need further study. Using three historical reanalysis data and multi scenario CMIP6 modeled data, Global Heat Wave Toolbox (GHWT) was developed to generate heat wave matrix from 1971 to 2100. The long-term changing characteristics of global heat waves were also analyzed. Next, population and GDP projections are employed to estimate future socioeconomic exposure and risks. The results show that except for high latitudes (latitude greater than 60°), high elevations and some coastal areas, heat waves have visited about 45% (±3%) of the global land area (excluding Antarctica). North Africa, North Australia, South Asia, and the Arabian Peninsula are detected as high heat wave area, where experience more than three heat waves with total duration over 15 days annually. Additionally, the average growth rate of global heat waves under SSP2 4.5 and SSP5 8.5 may be 2–3 times and 3–5 times of that under SSP1 2.6, respectively. Under SSP2 4.5, there may be about 7.32 billion people exposed to heat waves in 2100, accounting for 82.65% of the global population. Economic exposure may reach $433.37 trillion in 2100, accounting for 82.23% of the total global economy in that year. India could have the highest population and economic exposure, follow by populous countries, such as Pakistan and Bangladesh, and major economies, such as China and the United States. Under SSP1 2.6, the increase in heat waves may slow down significantly. Moreover, North Africa, Australia, and Brazil are identified as rapid heat wave growth area. Our study highlights the heat wave of future growth and its socioeconomic impacts, as well as the necessity for climate mitigation and adaptation measures.

To identify genes that respond to increased nitrogen and assess the involvement of the chlorophyll metabolic pathway and associated regulatory mechanisms in these responses, Nitraria tangutorum seedlings were subjected to four nitrogen concentrations (N0, N6, N36, and N60: 0, 6, 36, and 60 mmol·L−1 nitrogen, respectively). The N. tangutorum seedling leaf transcriptome was analyzed by high-throughput sequencing (Illumina HiSeq 4000), and 332,420 transcripts and 276,423 unigenes were identified. The numbers of differentially expressed genes (DEGs) were 4052 in N0 vs. N6, 6181 in N0 vs. N36, and 3937 in N0 vs. N60. Comparing N0 and N6, N0 and N36, and N0 and N60, we found 1101, 2222, and 1234 annotated DEGs in 113, 121, and 114 metabolic pathways, respectively, classified in the Kyoto Encyclopedia of Genes and Genomes database. Metabolic pathways with considerable accumulation were involved mainly in anthocyanin biosynthesis, carotenoid biosynthesis, porphyrin and chlorophyll metabolism, flavonoid biosynthesis, and amino acid metabolism. N36 increased δ-amino levulinic acid synthesis and upregulated expression of the magnesium chelatase H subunit, which promoted chlorophyll a synthesis. Hence, N36 stimulated chlorophyll synthesis rather than heme synthesis. These findings enrich our understanding of the N. tangutorum transcriptome and help us to research desert xerophytes’ responses to increased nitrogen in the future.

Global climate change affects biodiversity patterns, especially in arid and semi-arid regions such as the Mongolian plateau, one of the most ecologically fragile regions in the world. Three dynamic habitat indices (DHIs) were related to the productivity hypothesis and calculated based on FAPAR, including cumulative productivity (DHIcum indicates the availability of resources such as food supply and habitat in a year, representing available energy), minimum productivity (DHImin indicates the limitations of food and habitat resources in a year, representing environmental stress), and seasonal productivity (DHIsea denotes the change in productivity in a year, representing environmental stability). In this paper, we investigated the distribution pattern of species richness on the Mongolian Plateau based on the productivity hypothesis. We constructed models of the richness of three species (mammals, birds, and amphibians) using DHIs and climate variables to explain patterns of species richness on the Mongolian Plateau. The results revealed that, on the Mongolian plateau, there is a relatively high correlation between DHIs and species richness, especially with DHIcum (R = 0.59 for mammals, R = 0.73 for birds, and R = 0.58 for amphibians). There was a significant non-linear relationship between DHIs and species richness, as the model predictive power was significantly enhanced with GAM and RF. The inclusion of climate variables significantly improved the explanatory power of various models for the mammal, bird, and amphibian species richness on the Mongolian Plateau, with the best results for RF (0.89, 0.94, and 0.91, respectively). The influence of climate variables on species richness patterns in the importance ranking was higher than that of DHIs. Climate also has an influence on species richness. Vegetation productivity and climatic factors are good determinants of species richness on the Mongolian Plateau and should be carefully considered in future studies.

Disease risk is a persistent problem in domestic cattle farming, while economic traits are the main concern. This study aimed to reveal the epigenetic basis for differences between zebu (Bos indicus) and taurine cattle (Bos taurus) in disease, disease resistance, and economic traits, and provide a theoretical basis for the genetic improvement of domestic cattle. In this study, whole genome bisulfite sequencing (WGBS) was used to analyze the whole-genome methylation of spleen and liver samples from Yunnan zebu and Holstein cattle. In the genome-wide methylation pattern analysis, it was found that the methylation pattern of all samples was dominated by the CG type, which accounted for >94.9%. The DNA methylation levels of different functional regions and transcriptional elements in the CG background varied widely. However, the methylation levels of different samples in the same functional regions or transcriptional elements did not differ significantly. In addition, we identified a large number of differentially methylation region (DMR) in both the spleen and liver groups, of which 4713 and 4663 were annotated to functional elements, and most of them were annotated to the intronic and exonic regions of genes. GO and KEGG functional analysis of the same differentially methylation region (DMG) in the spleen and liver groups revealed that significantly enriched pathways were involved in neurological, disease, and growth functions. As a result of the results of DMR localization, we screened six genes (DNM3, INPP4B, PLD, PCYT1B, KCNN2, and SLIT3) that were tissue-specific candidates for economic traits, disease, and disease resistance in Yunnan zebu. In this study, DNA methylation was used to construct links between genotypes and phenotypes in domestic cattle, providing useful information for further screening of epigenetic molecular markers in zebu and taurine cattle.

Enhancers are often transcribed into non-coding RNAs called enhancer RNAs. Here the authors show that super enhancer generated seRNA-1 regulates the expression of nearby myoglobin (Mb) gene by binding to heterogeneous nuclear ribonucleoprotein L during myogenic differentiation.

The species composition and diversity pattern of leaf miners on dominant trees in China are poorly understood. Using Hill-based diversity metrics, the elevational patterns of taxonomic, phylogenetic, and functional diversity for leaf miners on Quercus variabilis Blume at Baotianman were systematically analyzed. Leaf mine types belonged to ten genera and seven families. Different leaf miners had different elevational preferences. Most taxonomic and phylogenetic Hill diversity indices had typical hump-shaped elevational patterns, with a peak at the middle elevation of approximately 875 m. No functional Hill diversity indices presented significant linear or nonlinear trends with altitude. The driving factors behind the elevational distribution patterns of leaf miners require further work.

The important effect of climate factors on spring phenology has been confirmed by numerous studies, but its temporal variation remains unclear. Based on the daily meteorological observation data and annual vegetation phenology data from 1987 to 2016, this study proposes a Time Window Sliding Fitting (TWSF) method. Partial Least Squares (PLS) regression is used to investigate the relationship between spring phenology and five climate factors, including mean temperature, total precipitation, mean photoperiod, chilling index and forcing index, in all time windows from December to next May with 7-day interval in Qinling Mountains (QLMs) of China. The results show that: (1) Temperature in QLMs has an increasing trend with 0.41 °C/10a, and precipitation decreases with 400 mm/a. Moreover, spring phenology in QLMs is advancing with 4 days/10a. (2) Temperature is found having dominant effect on spring phenology in QLMs, and photoperiod has a significant effect on spring phenology in grassland area. (3) Temperature’s impact increases in cultivated land and grassland after March 25 but a consecutive decrease trend in forest, while photoperiod’s explanatory ability on grassland spring phenology is highlighted in early January, early February and early April. Chilling has the best explanatory ability on crop spring phenology in early March and early May. Additionally, forcing can significantly influence spring phenology in early March for cultivated land and late May for forest. The results of this study are beneficial to understand the mechanism of plant-climate interaction.

The N6-methyladenosine (m6A) is the most abundant internal modification in advanced eukaryotic mRNAs, and it plays an important role in mRNA metabolism and diverse biological processes. Moreover, m6A modification is dynamically reversible and may reshape gene expression patterns after demethylation induced by drug interventions, which may reverse the occurrence and progression of certain diseases. Although the role of changes in DNA methylation in ophthalmic diseases has been well described, the regulatory role of the m6A modification in ophthalmic diseases is still a new field of study. This paper aims to systematically summarize the latest research progress about m6a-modification-related ophthalmic diseases and potential therapeutic strategies. All English literature relevant to our research was searched in PubMed and CNKI databases, using appropriate keywords. Our study reviews the regulatory role of m6A in ophthalmic diseases. It covers almost all of the reported m6A-related ophthalmic diseases and proposes potential treatment strategies for each disease. This review will provide direction for further research on m6A in ophthalmic diseases and help in the treatment of ophthalmic diseases in the future.

Persistent infection with human papillomavirus (HPV) and immune surveillance failure may be the initiating factors for the carcinogenesis of cervical squamous cell carcinoma (CSCC). HPV infection might affect the innate immune pathway of cervical epithelial cells that constitute the “microenvironment” for tumor cells. Programmed death-ligand 1 (PD-L1) has been reported to be an immunosuppressor that helps cancer cells escape the actions of T cells. In the present study, CXCL10 was substantially upregulated both in cervical tissues of HPV infected patients with cervical intraepithelial neoplasia (CIN) or CSCC, as well as in HPV16 E6/E7 transgenic murine cervix. The HPV-positive (HPV+) cervical cancer cell lines SiHa and Caski secreted increased levels of CXCL10 compared to human foreskin fibroblasts (HFF-1), and its receptor CXCR3 was overexpressed in HFF-1. After co-culture with SiHa or Caski, the JAK-STAT signaling pathway and exosomal PD-L1 expression were both upregulated in HFF-1. Recombinant human CXCL10 induced JAK-STAT and PD-L1, while the CXCL10-CXCR3 and JAK-STAT inhibitors AMG487 or ruxolitinib reduced the expression of PD-L1 in HFF-1 cells. Furthermore, the upregulated expression of PD-L1 was verified in HPV+ but not HPV-negative (HPV-) patients with cervical cancers by analysis of tissue microarray cores in 25 cervical lesion patients (P < 0.05). The results indicate that HPV infection can induce cervical cancer cells to secrete CXCL10, which binds to CXCR3 in the surrounding fibroblast cells,leading to JAK-STAT pathway activation and the subsequent upregulated expression of exosomal PD-L1. These mechanisms may help HPV to escape immune response attack, leading to carcinogenesis.

The flunixin residues in foods of animal origin could pose hazards for human health. In this paper, a broad-selectivity polyclonal antibody was obtained using 5-hydroxyflunixin coupled with bovine serum albumin as the immunogen. The semi-inhibitory concentration (IC50) of the polyclonal antibody was 1.43 ng/mL for flunixin and 0.29 ng/mL for 5-hydroxyflunixin, respectively, which were far below the maximum residue limits set by the United States, the European Union and China. The limits of detection were calculated to be 2.98 μg/kg for flunixin in bovine muscle and 0.78 μg/L for 5-hydroxyflunixin in milk. In spike and recovery tests, the average recovery ranged from 83% to 105%, with a satisfying coefficient of variance ranging from 5.8% to 11.3%. Furthermore, the ELISA method was validated by a well-established LC-MS/MS method. These results proved that the established method is suitable for flunixin and 5-hydroxyflunixin residue analysis.

As one of the earliest remote sensing indices, the Normalized Difference Vegetation Index (NDVI) has been employed extensively for vegetation research. However, despite an abundance of NDVI review articles, these studies are predominantly limited to either one subject area or one area, with systematic NDVI reviews being relatively rare. Bibliometrics is a useful method of analyzing scientific literature that has been widely used in many disciplines; however, it has not yet been applied to comprehensively analyze NDVI research. Therefore, we used bibliometrics and scientific mapping methods to analyze citation data retrieved from the Web of Science during 1985–2021 with NDVI as the topic. According to the analysis results, the amount of NDVI research increased exponentially during the study period, and the related research fields became increasingly varied. Moreover, a greater number of satellite and aerial remote sensing platforms resulted in more diverse NDVI data sources. In future, machine learning methods and cloud computing platforms led by Google Earth Engine will substantially improve the accuracy and production efficiency of NDVI data products for more effective global research.

Glucose oxidase, which uses molecular oxygen as an electron acceptor to specifically catalyze the conversion of β-d-glucose to gluconic acid and hydrogen peroxide (H2O2), has been considered an important enzyme in increasing environmental sustainability and food security. However, achieving the high yield, low price and high activity required for commercial viability remains challenging. In this review, we first present a brief introduction, looking at the sources, characteristics, catalytic process, and applications of glucose oxidase. Then, the predictive structures of glucose oxidase from two different sources are comparatively discussed. We summarize the inhibitors of glucose oxidase. Finally, we highlight how the production of glucose oxidase can be improved by optimizing the culture conditions and microbial metabolic engineering.

The start of the growing season (SOS) is a vital ecological indicator for climate change and the terrestrial ecosystem. Previous studies have reported that the SOS over the Northern Hemisphere (NH) has experienced remarkable changes in the past few decades. However, because of the different spatial and temporal coverages of existing SOS studies, a coherent and robust account for SOS changes in the NH has been lacking. Using satellite-retrieved vegetation-phenology datasets, ground observations, and several auxiliary datasets, this study evaluated the performance of the latest MODIS vegetation-dynamics dataset (MCD12Q2-C6) and explored the distribution and attribution of the SOS to climate change over the NH for the period 2001–2018. The validation results using the Chinese Ecosystem Research Network (CERN) and Lilac-leafing observations (Lilac) displayed that the MCD12Q2-C6 has a good performance in SOS monitoring over the NH mid-latitudes. Meanwhile, evidence from MCD12Q2-C6 pointed out that the SOS was advanced by 2.08 days on average over the NH during 2001–2018, especially for Europe, China, and Alaska, United States. In addition, detailed-sensitivity analysis showed that the increased surface air temperature (Ts) (−1.21 ± 0.34 days °C−1) and reduced snow-cover fraction (Sc) (0.62 ± 0.29 days%−1) were the key driving factors of the observed SOS changes over the NH during 2001–2018. Compared with Ts and Sc, the role of total precipitation (Pt) was minor in dominating the spring vegetation-phenology changes at the same period. The findings of this study contribute to our understanding of the responses of SOS to the competing changes of Ts, Pt, and Sc over the NH.

Drought resistance in plants is controlled by multiple genes. To identify the genes that mediate drought stress responses and to assess the associated metabolic pathways in the desert shrub Nitraria tangutorum, we conducted a transcriptome analysis of plants under control (maximum field capacity) and drought (20% of the maximum field capacity) conditions. We analyzed differentially expressed genes (DEGs) of N. tangutorum and their enrichment in the KEGG metabolic pathways database, and explored the molecular biological mechanisms underlying the answer to its drought tolerance. Between the control and drought groups, 119 classified metabolic pathways annotated 3047 DEGs in the KEGG database. For drought tolerance, nitrate reductase (NR) gene expression was downregulated, indicating that NR activity was decreased to improve drought tolerance. In ammonium assimilation, drought stress inhibited glutamine formation. Protochlorophyllide reductase (1.3.1.33) expression was upregulated to promote chlorophyll a synthesis, whereas divinyl reductase (1.3.1.75) expression was downregulated to inhibit chlorophyll-ester a synthesis. The expression of the chlorophyll synthase (2.5.1.62) gene was downregulated, which affected the synthesis of chlorophyll a and b. Overall, drought stress appeared to improve the ability to convert chlorophyll b into chlorophyll a. Our data serve as a theoretical foundation for further elucidating the growth regulatory mechanism of desert xerophytes, thereby facilitating the development and cultivation of new, drought-resistant genotypes for the purpose of improving desert ecosystems.

Atherosclerosis (AS), the most common underlying pathology for coronary artery disease, is a chronic inflammatory, proliferative disease in large- and medium-sized arteries. The vascular endothelium is important for maintaining vascular health. Endothelial dysfunction is a critical early event leading to AS, which is a major risk factor for stroke and myocardial infarction. Accumulating evidence has suggested the critical roles of histone deacetylases (HDACs) in regulating vascular cell homeostasis and AS. The purpose of this review is to present an updated view on the roles of HDACs (Class I, Class II, Class IV) and HDAC inhibitors in vascular dysfunction and AS. We also elaborate on the novel therapeutic targets and agents in atherosclerotic cardiovascular diseases.

Snow-induced radiative forcing (SnRF), defined as the instantaneous perturbation of the Earth’s shortwave radiation at the top of the atmosphere (TOA), results from variations in the terrestrial snow cover extent (SCE), and is critical for the regulation of the Earth’s energy budget. However, with the growing seasonal divergence of SCE over the Northern Hemisphere (NH) in the past two decades, novel insights pertaining to SnRF are lacking. Consequently, the contribution of SnRF to TOA shortwave radiation anomalies still remains unclear. Utilizing the latest datasets of snow cover, surface albedo, and albedo radiative kernels, this study investigated the distribution of SnRF over the NH and explored its changes from 2000 to 2019. The 20-year averaged annual mean SnRF in the NH was −1.13 ± 0.05 W m−2, with a weakening trend of 0.0047 Wm−2 yr−1 (p < 0.01) during 2000–2019, indicating that an extra 0.094 W m−2 of shortwave radiation was absorbed by the Earth climate system. Moreover, changes in SnRF were highly correlated with satellite-observed TOA shortwave flux anomalies (r = 0.79, p < 0.05) during 2000–2019. Additionally, a detailed contribution analysis revealed that the SnRF in snow accumulation months, from March to May, accounted for 58.10% of the annual mean SnRF variability across the NH. These results can assist in providing a better understanding of the role of snow cover in Earth’s climate system in the context of climate change. Although the rapid SCE decline over the NH has a hiatus for the period during 2000–2019, SnRF continues to follow a weakening trend. Therefore, this should be taken into consideration in current climate change models and future climate projections.

Abstract The speeds of both Arctic surface warming and sea-ice shrinking have accelerated over recent decades. However, the causes of this unprecedented phenomenon remain unclear and are subjects of considerable debate. In this study, we report strong observational evidence, for the first time from long-term (1984–2014) spatially complete satellite records, that increased cloudiness and atmospheric water vapor in winter and spring have caused an extraordinary downward longwave radiative flux to the ice surface, which may then amplify the Arctic wintertime ice-surface warming. In addition, we also provide observed evidence that it is quite likely the enhancement of the wintertime greenhouse effect caused by water vapor and cloudiness has advanced the time of onset of ice melting in mid-May through inhibiting sea-ice refreezing in the winter and accelerating the pre-melting process in the spring, and in turn triggered the positive sea-ice albedo feedback process and accelerated the sea ice melting in the summer.

Snow cover phenology has exhibited dramatic changes in the past decades. However, the distribution and attribution of the hemispheric scale snow cover phenology anomalies remain unclear. Using satellite-retrieved snow cover products, ground observations, and reanalysis climate variables, this study explored the distribution and attribution of snow onset date, snow end date, and snow duration days over the Northern Hemisphere from 2001 to 2020. The latitudinal and altitudinal distributions of the 20-year averaged snow onset date, snow end date, and snow duration days are well represented by satellite-retrieved snow cover phenology matrixes. The validation results by using 850 ground snow stations demonstrated that satellite-retrieved snow cover phenology matrixes capture the spatial variability of the snow onset date, snow end date, and snow duration days at the 95% significance level during the overlapping period of 2001–2017. Moreover, a delayed snow onset date and an earlier snow end date (1.12 days decade−1, p < 0.05) are detected over the Northern Hemisphere during 2001–2020 based on the satellite-retrieved snow cover phenology matrixes. In addition, the attribution analysis indicated that snow end date dominates snow cover phenology changes and that an increased melting season temperature is the key driving factor of snow end date anomalies over the NH during 2001–2020. These results are helpful in understanding recent snow cover change and can contribute to climate projection studies.

Vegetation phenology in spring has received much attention for its importance to terrestrial ecosystem carbon exchange and climate–biosphere interactions studies. Through control on surface water and heat balance, snow cover largely impacts on spring vegetation phenology. However, under the background of global warming and rapid reduction of spring snow cover extent across the Northern Hemisphere (NH), the responses of spring vegetation phenology have not been well documented. Using two satellite-derived land cover dynamic datasets and 420 in situ vegetation phenology observations from five filed datasets, this study evaluated the accuracy of satellite-derived vegetation phenology datasets and explored the changes of start of the growing season (SOS) across the NH snow-covered landmass for the period 2001–2014. Compared with MEaSUREs VIPPHEN, the MODIS SOS maps displayed higher accuracy in capture the real SOS climatology by validating with in situ observations ( R ^2 = 0.67, bias = −3.99 d). Moreover, evidences from MODIS SOS maps pointed out that the SOS advanced by approximately 2.36 d in NH middle to high latitudes (43.5°N–70.0°N), but delayed by about 0.53 d in lower latitudes (33.0°N–43.5°N) from 2001 to 2014. The contrast SOS anomalies across the NH snow-covered landmass were further proved by changes in spring NDVI derived from GIMMS in the corresponding period. In addition, the observed changes in SOS were consistent with the spatiotemporal pattern of spring snow end date found in previous studies, indicating vegetation phenology changes should be taken into account in estimating the impacts of snow in climate–biosphere interactions studies.

Monitoring surface albedo at medium-to-fine resolution (

Chlorophyll is the most important component of crop photosynthesis, and the reviving stage is an important period during the rapid growth of winter wheat. Therefore, rapid and precise monitoring of chlorophyll content in winter wheat during the reviving stage is of great significance. The satellite-UAV-ground integrated inversion method is an innovative solution. In this study, the core region of the Yellow River Delta (YRD) is used as a study area. Ground measurements data, UAV multispectral and Sentinel-2A multispectral imagery are used as data sources. First, representative plots in the Hekou District were selected as the core test area, and 140 ground sampling points were selected. Based on the measured SPAD values and UAV multispectral images, UAV-based SPAD inversion models were constructed, and the most accurate model was selected. Second, by comparing satellite and UAV imagery, a reflectance correction for satellite imagery was performed. Finally, based on the UAV-based inversion model and satellite imagery after reflectance correction, the inversion results for SPAD values in multi-scale were obtained. The results showed that green, red, red-edge and near-infrared bands were significantly correlated with SPAD values. The modeling precisions of the best inversion model are R2 = 0.926, Root Mean Squared Error (RMSE) = 0.63 and Mean Absolute Error (MAE) = 0.92, and the verification precisions are R2 = 0.934, RMSE = 0.78 and MAE = 0.87. The Sentinel-2A imagery after the reflectance correction has a pronounced inversion effect; the SPAD values in the study area were concentrated between 40 and 60, showing an increasing trend from the eastern coast to the southwest and west, with obvious spatial differences. This study synthesizes the advantages of satellite, UAV and ground methods, and the proposed satellite-UAV-ground integrated inversion method has important implications for real-time, rapid and precision SPAD values collected on multiple scales.