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Abstract This study aimed to explore physicians’ and pharmacists’ knowledge, attitudes, and practice (KAP) regarding the prevention and treatment of cardiovascular toxicity associated with cancer treatment. A multicenter cross-sectional study included physicians and pharmacists between April 2023 and June 2023. The study included 918 participants (514 physicians and 404 pharmacists). The average scores of knowledge, attitudes, and practice were 11.6 ± 3.39, 24.7 ± 2.6, and 26.3 ± 6.8 points. Sufficient knowledge was significantly associated with age ≥ 41 years (odds ratio (OR) = 2.745, 95% confidence interval (CI) 1.086–6.941, P = 0.033), male (OR = 2.745, 95% CI 1.150–2.223, P = 0.005), bachelor’s degree (OR = 0.084, 95% CI 0.013–0.533, P = 0.009), master’s degree and above (OR = 0.096, 95% CI 0.015–0.609, P = 0.013), physician occupation (OR = 7.601, 95% CI 1.337–43.207, P = 0.022), pharmacy department (OR = 18.858, 95% CI 3.245–109.57, P = 0.001), oncology department (OR = 4.304, 95% CI 2.426–7.634, P

With the rapid development of modern information technology and network technology, the construction of tax informatization plays an important role in improving the level of tax management and work efficiency. However, in the centralized data processing mode, the establishment of large data center and the efficient, stable, and secure connection of server bandwidth have become key challenges. Moreover, the openness and interconnectivity of the tax system network pose various network security threats, seriously threatening the integrity and security of data. For the above issues, this article proposes a tax system network security protection scheme based on elliptic curve cryptography. This scheme combines hash function and elliptic curve cryptography to achieve user anonymity and secure generation of session keys, effectively ensuring the secure transmission of confidential information. The security and effectiveness of the scheme are verified through informal and formal security analysis based on security proof, BAN logic and AVISPA tool. And a comprehensive evaluation of the scheme is conducted, and the results show that the scheme significantly reduced the costs while providing security features.

The peel stripe margin pattern is one of the most important quality traits of watermelon. In this study, two contrasted watermelon lines [slb line (P1) with a clear peel stripe margin pattern and GWAS-38 line (P2) with a blurred peel stripe margin pattern] were crossed, and biparental F2 mapping populations were developed. Genetic segregation analysis revealed that a single recessive gene is modulating the main-effect genetic locus (Clcsm) of the clear stripe margin pattern of peel. Bulked segregant analysis-based sequencing (BSA-Seq) and fine genetic mapping exposed the delimited Clcsm locus to a 19.686-kb interval on chromosome 6, and the Cla97C06G126680 gene encoding the MYB transcription factor family was identified. The gene mutation analysis showed that two non-synonymous single-nucleotide polymorphism (nsSNP) sites [Chr6:28438793 (A-T) and Chr6:28438845 (A-C)] contribute to the clear peel stripe margin pattern, and quantitative real-time polymerase chain reaction (qRT-PCR) also showed a higher expression trend in the slb line than in the GWAS-38 line. Further, comparative transcriptomic analysis identified major differentially expressed genes (DEGs) in three developmental periods [4, 12, and 20 days after pollination (DAP)] of both parental lines. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses indicated highly enriched DEGs involved in metabolic processes and catalytic activity. A total of 44 transcription factor families and candidate genes belonging to the ARR-B transcription factor family are believed to regulate the clear stripe margin trait of watermelon peel. The gene structure, sequence polymorphism, and expression trends depicted significant differences in the peel stripe margin pattern of both parental lines. The ClMYB36 gene showed a higher expression trend for regulating the clear peel stripe margin of the slb line, and the ClAPRR5 gene depicted a higher expression for modulating the blurred peel stripe margin in the GWAS-38 line. Overall, our fine genetic mapping and transcriptomic analysis revealed candidate genes differentiating the clear and blurred peel stripe patterns of watermelon fruit.

Abstract Background S. pyogenes, is a primary pathogen that leads to pharyngitis and can also trigger severe conditions like necrotizing fasciitis and streptococcal toxic shock syndrome (STSS), often resulting in high mortality rates. Therefore, prompt identification and appropriate treatment of S. pyogenes infections are crucial in preventing the worsening of symptoms and alleviating the disease's impact. Results In this study, a newly developed technique called multiple cross displacement amplification (MCDA) was employed to detect S. pyogenes,specifically targeting the speB gene, at a temperature of 63°C within 30 min. Then, an easily portable and user-friendly nanoparticles-based lateral flow biosensor (LFB) assay was introduced for the rapid analysis of MCDA products in just 2 min. The results indicated that the LFB offers greater objectivity compared to Malachite Green and is simpler than electrophoresis. The MCDA-LFB assay boasts a low detection limit of 200 fg and exhibits no cross-reaction with non-S. pyogenes strains. Among 230 clinical swab throat samples, the MCDA-LFB method identified 27 specimens as positive, demonstrating higher sensitivity compared to 23 samples detected positive by qPCR assay and 18 samples by culture. The only equipment needed for this assay is a portable dry block heater. Moreover, each MCDA-LFB test is cost-effective, priced at approximately $US 5.5. Conclusion The MCDA-LFB assay emerges as a straightforward, specific, sensitive, portable, and user-friendly method for the rapid diagnosis of S. pyogenes in clinical samples.

Three types of aggregate, including metallurgical slag aggregate (steel slag, copper slag, and iron sand), rare earth porcelain sand (REPS) aggregate as artificial aggregate, and recycled aggregate, were selected to produce concrete with the same basic mixture proportions in order to investigate the influence of aggregate types and aggregate replacement rates on their mechanical properties. Three levels of aggregate replacement rate—20%, 35%, and 50% for coarse aggregate (CA) and 20%, 30%, and 40% for fine aggregate (FA)—were employed in this study. The results indicate that replacing natural sand with metallurgical slag aggregate as FA enhances the mechanical properties of concrete. Among these, iron sand (IS) shows superior enhancement effects compared with copper slag (CS), and CS outperforms steel slag (SS). Specifically, at a 30% IS replacement rate, the compressive strength and splitting tensile strength of IS aggregate concrete are 32.8% and 35.6% higher than those of natural aggregate concrete, respectively. REPS used as CA demonstrates significant improvements in compressive strength, while REPS used as FA notably enhances splitting tensile strength. For recycled aggregate concrete with recycled coarse aggregate replacement rates of 35% and 50%, mechanical properties are effectively strengthened by incorporating CS as FA at a 30% replacement rate and REPS as CA at a 20% substitution ratio, respectively. Additionally, XRF and XRD techniques were employed to confirm aggregate composition and were combined with SEM and EDS techniques to analyze the concrete microstructure, clarifying the strengthening mechanisms of metallurgical and artificial aggregates on concrete.

Vapor pressure deficit (VPD) shows significant spatial and temporal variability in the context of global climate change, which is important for studying the implications of climate change on the structure and function of ecosystems to analyze the effects of VPD on vegetation dynamics. Spatial patterns of vegetation sensitivity to VPD have been recently investigated, however, the feedback of different vegetation types to VPD may vary depending on physiological characteristics, it is unclear how different types influence the sensitivity to VPD. In this study, the ERA5-Land reanalysis time-series dataset was used to analyze the spatial and temporal trends of VPD under different vegetation types. It was found that VPD showed an increasing trend in vegetated areas over the past 20 years with large spatial heterogeneity, generally increasing with drying conditions. On this basis, the spatial patterns of vegetation sensitivity to VPD and temporal trends in sensitivity were evaluated over the past 20 years in China using the enhanced vegetation index (EVI) and near-infrared reflectance of vegetation (NIRv) which can describe vegetation dynamics. The results show that the sensitivities under the two indices have high spatial consistency, with northeastern and central China showing positive sensitivities and southern China showing negative sensitivities, respectively. The positive sensitivities are relatively high for Deciduous Broadleaf Forests (DBF), Deciduous Needleleaf Forests (DNF), Grasslands (GL), and Croplands (CL) types, while the negative sensitivities are larger for Shrublands (SL) and Savannas (SA) types. Under different climatic zones, the sensitivity of CL and GL are independent of climatic zones (both showing positive), while the sensitivity of SL is negative in the Humid zone and positive in the Semi-Arid zone. Temporally, the sensitivity showed a slow increasing trend over the last 20 years. In terms of vegetation types, sensitivities of Evergreen Broadleaf Forests (EBF), DBF, GL and CL types showed a significant increasing trend (p

Abstract CDK4/6 are important regulators of cell cycle and their inhibitors have been approved as anti-cancer drugs. Here, we report a STING-dependent anti-tumor immune mechanism responsible for tumor suppression by CDK4/6 blockade. Clinical datasets show that in human tissues, CDK4 and CDK6 are over-expressed and their expressions are negatively correlated with patients’ overall survival and T cell infiltration. Deletion of Cdk4 or Cdk6 in tumor cells significantly reduce tumor growth. Mechanistically, we find that Cdk4 or Cdk6 deficiency contributes to an increased level of endogenous DNA damage, which triggers the cGAS-STING signaling pathway to activate type I interferon response. Knockout of Sting is sufficient to reverse and partially reverse the anti-tumor effect of Cdk4 and Cdk6 deficiency respectively. Therefore, our findings suggest that CDK4/6 inhibitors may enhance anti-tumor immunity through the STING-dependent type I interferon response.

The Yellow River Basin (YB) acts as a key barrier to ecological security and is an important experimental region for high-quality development in China. There is a growing demand to assess the ecological status in order to promote the sustainable development of the YB. The eco-environmental quality (EEQ) of the YB was assessed at both the regional and provincial scales utilizing the remote sensing-based ecological index (RSEI) with Landsat images from 2000 to 2020. Then, the Theil–Sen (T-S) estimator and Mann–Kendall (M-K) test were utilized to evaluate its variation trend. Next, the optimal parameter-based geodetector (OPGD) model was used to examine the drivers influencing the EEQ in the YB. Finally, the geographically weighted regression (GWR) model was utilized to further explore the responses of the drivers to RSEI changes. The results suggest that (1) a lower RSEI value was found in the north, while a higher RSEI value was found in the south of the YB. Sichuan (SC) and Inner Mongolia (IM) had the highest and the lowest EEQ, respectively, among the YB provinces. (2) Throughout the research period, the EEQ of the YB improved, whereas it deteriorated in both Henan (HA) and Shandong (SD) provinces. (3) The soil-available water content (AWC), annual precipitation (PRE), and distance from impervious surfaces (IMD) were the main factors affecting the spatial differentiation of RSEI in the YB. (4) The influence of meteorological factors (PRE and TMP) on RSEI changes was greater than that of IMD, and the influence of IMD on RSEI changes showed a significant increasing trend. The research results provide valuable information for application in local ecological construction and regional development planning.

Marine heatwave (MHW) events have significant consequences for marine ecosystems and human society. This paper investigates a MHW’s spatial–temporal characteristics in the Changjiang River Estuary and its surrounding coastal regions (CRESs), as well as analyzes the drivers, using satellite and reanalysis data spanning from 1982–2021. The findings show that, during the last 40 years, all four of the MHW indicators have increased. The summer MHW is more severe than other seasons, showing a rising pattern from southeast to northwest. The rise of MHWs can be attributed to the increase in sea surface heat flux, weak wind speed, and powerful El Niño events. Additionally, two special MHW events were detected during the entire study period: Event A lasted for 191 days from 9 October 2006 to 17 April 2007; Event B had an average intensity of 4.93 °C from 5 July 1994 to 1 August 1994. For locations so close to each other, the characteristics of MHWs can also vary, and the mechanisms behind them are highly complex.

Summary: Long non-coding RNAs (lncRNAs) have been implicated in diverse biological processes. However, the functional mechanisms have not yet been fully explored. Characterizing the interactions of lncRNAs with chromatin is central to determining their functions but, due to precise and efficient approaches lacking, our understanding of their functional mechanisms has progressed slowly. In this study, we demonstrate that a nuclear lncRNA linc1393 maintains mouse ESC pluripotency by recruiting SET1A near its binding sites, to establish H3K4me3 status and activate the expression of specific pluripotency-related genes. Moreover, we characterized the principles of lncRNA–chromatin interaction and transcriptional regulation. Accordingly, we developed a computational framework based on the XGBoost model, LncTargeter, to predict the targets of a given lncRNA, and validated its reliability in various cellular contexts. Together, these findings elucidate the roles and mechanisms of lncRNA on pluripotency maintenance, and provide a promising tool for predicting the regulatory networks of lncRNAs.

Near-surface air temperature (NSAT) is an important environmental parameter; however, there is a lack of long-term, fine-scale NSAT products that offer complete spatiotemporal continuity. Although several available products cover different periods and regions, obtaining gridded NSAT data outside of the provided regions and periods remains challenging. Using multiple source data (ERA5-Land, global land data assimilation system, remotely-sensed data, and several auxiliary factors), a new high-efficient framework for estimating NSAT is presented using the random forest algorithm and implemented on the Google Earth Engine platform in this study. Thereby, the 1-km daily seamless NSAT product (containing daily maximum, mean, and minimum) from January 1st 1981 to December 31st 2020 over the Yellow River Basin in China is generated. To our knowledge, this is the first product that satisfies the conditions of high resolution, seamless coverage, and long-term continuity simultaneously for the Yellow River Basin. Tenfold cross validation shows that the RMSE, MAE, and R2 for the maximum NSAT are 1.746–1.932 K, 1.351–1.486 K, and 0.968–0.974, respectively; for the mean NSAT are 1.219–1.354 K, 0.940–1.035 K, and 0.984–0.987; and for the minimum daily NSAT are 1.663–1.732 K, 1.280–1.322 K, and 0.975–0.997. In addition, a user-friendly NSAT estimation tool was developed for the first time, enabling users to derive NSAT products for specific areas and time periods of interest. Evaluation of the tool indicates that the accuracy of temporally extended NSAT is satisfactory, while the accuracy of spatially extended NSAT is lower compared to the original region. The generated long-term finer-scale NSAT product and the developed NSAT estimation tool hold potential benefits for ecoclimate researchers and environmental policy makers.

Abstract Metabolism feeds into the regulation of epigenetics via metabolic enzymes and metabolites. However, metabolic features, and their impact on epigenetic remodeling during mammalian pre-implantation development, remain poorly understood. In this study, we established the metabolic landscape of mouse pre-implantation embryos from zygote to blastocyst, and quantified some absolute carbohydrate metabolites. We integrated these data with transcriptomic and proteomic data, and discovered the metabolic characteristics of the development process, including the activation of methionine cycle from 8-cell embryo to blastocyst, high glutaminolysis metabolism at blastocyst stage, enhanced TCA cycle activity from the 8-cell embryo stage, and active glycolysis in the blastocyst. We further demonstrated that oxidized nicotinamide adenine dinucleotide (NAD+) synthesis is indispensable for mouse pre-implantation development. Mechanistically, in part, NAD+ is required for the exit of minor zygotic gene activation (ZGA) by cooperating with SIRT1 to remove zygotic H3K27ac. In human, NAD+ supplement can promote the removal of zygotic H3K27ac and benefit pre-implantation development. Our findings demonstrate that precise and timely regulation of minor ZGA is controlled by metabolic dynamics, and enhance our understanding of the metabolism of mammalian early embryos.

This paper proposes a dual-weighted polarization image fusion method based on quality assessment and attention mechanisms to fuse the intensity image (S0) and the degree of linear polarization (DoLP). S0 has high contrast and clear details, and DoLP has an outstanding ability to characterize polarization properties, so the fusion can achieve an effective complementation of superior information. We decompose S0 and DoLP into base layers and detail layers. In the base layers, we build a quality assessment unit combining information entropy, no-reference image quality assessment, and local energy to ensure the fused image has high contrast and clear and natural visual perception; in the detail layer, we first extract depth features using the pre-trained VGG19, then construct an attention enhancement unit combining space and channels, and finally effectively improve the preservation of detail information and edge contours in the fused image. The proposed method is able to perceive and retain polarization image features sufficiently to obtain desirable fusion results. Comparing nine typical fusion methods on two publicly available and own polarization datasets, experimental results show that the proposed method outperforms other comparative algorithms in both qualitative comparison and quantitative analysis.

NX toxins have been described as a novel group of type A trichothecenes produced by members of the Fusarium graminearum species complex (FGSC). Differences in structure between NX toxins and the common type B trichothecenes arise from functional variation in the trichothecene biosynthetic enzyme Tri1 in the FGSC. The identified highly conserved changes in the Tri1 gene can be used to develop specific PCR-based assays to identify the NX-producing strains. In this study, the sequences of the Tri1 gene from type B trichothecene- and NX-producing strains were analyzed to identify DNA polymorphisms between the two different kinds of trichothecene producers. Four sets of Polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) methods were successfully developed to distinguish the common type B trichothecene producers and NX producers within FGSC. These promising diagnostic methods can be used for high-throughput genotype detection of Fusarium strains as a step forward for crop disease management and mycotoxin control in agriculture. Additionally, it was found that the Tri1 gene phylogeny differs from the species phylogeny, which is consistent with the previous studies.

Fusarium heading blight (FHB) is a devastating disease in wheat, primarily caused by field invasion of Fusarium graminearum. Due to the scarcity of resistant wheat varieties, the agricultural sector resorts to chemical fungicides to control FHB incidence. On the other hand, biocontrol represents a promising, eco-friendly approach aligned with sustainable and green agriculture concepts. In the present study, a bacterial endophyte, Pseudescherichia sp. (GSE25), was isolated from wheat seeds and identified through complete genome sequencing and phylogenetic analysis. In vitro testing of this endophytic strain demonstrated strong antifungal activity against F. graminearum PH-1 by inhibiting spore germination, suppressing germ tube growth, and causing cell membrane damage. Under field conditions, the strain GSE25 significantly reduced the FHB incidence and the associated deoxynivalenol mycotoxin accumulation by over 60% and 80%, respectively. These findings highlight the potential of the isolated bacterial endophyte Pseudescherichia sp. GSE25 strain as a biocontrol agent in protecting wheat from FHB-caused F. graminearum. This is the first report showing a biocontrol effect of Pseudescherichia sp. a strain against phytopathogens.

Understanding the effects of natural and human disturbance factors on fractional vegetation coverage (FVC) is significant in the promotion of ecological and environmental protection. However, most of the relevant studies neglect to consider differences in the effect of driving factors on areas with different vegetation change characteristics. In this paper, we have combined Theil-Sen median trend analysis and Mann-Kendall testing to identify degraded and restored areas. Differences in the impact of various factors on FVC in terms of degradation, restoration, and the whole region were distinguished quantitatively using the geodetector model. Additionally, the constraint line approach was used to detect the influence thresholds of factors on FVC. The results are shown as below: (1) FVC showed an overall improving trend, and vegetation restoration and degradation areas accounted for 69.2% and 22.0%, respectively. (2) The two dominant factors affecting FVC were Digital Elevation Model (DEM) and temperature for both degraded and restored regions. However, the explanatory power of precipitation was noticeably different between regions. (3) Most natural factors had a “convex” constraint effect on FVC, which gradually weakened with an increase in the variable below the threshold and vice versa. Human disturbance factors negatively constrained FVC, and the constraint effect increased with increased human activity. This study can help decision-makers optimize specific implementation policies relating to ecological restoration and sustainable development.

Abstract Background Neutralizing antibodies are approved drugs to treat coronavirus disease-2019 (COVID-19) patients, yet mutations in severe acute respiratory syndrome coronavirus (SARS-CoV-2) variants may reduce the antibody neutralizing activity. New monoclonal antibodies (mAbs) and antibody remolding strategies are recalled in the battle with COVID-19 epidemic. Results We identified multiple mAbs from antibody phage display library made from COVID-19 patients and further characterized the R3P1-E4 clone, which effectively suppressed SARS-CoV-2 infection and rescued the lethal phenotype in mice infected with SARS-CoV-2. Crystal structural analysis not only explained why R3P1-E4 had selectively reduced binding and neutralizing activity to SARS-CoV-2 variants carrying K417 mutations, but also allowed us to engineer mutant antibodies with improved neutralizing activity against these variants. Thus, we screened out R3P1-E4 mAb which inhibits SARS-CoV-2 and related mutations in vitro and in vivo. Antibody engineering improved neutralizing activity of R3P1-E4 against K417 mutations. Conclusion Our studies have outlined a strategy to identify and engineer neutralizing antibodies against SARS-CoV-2 variants.

Watermelon fruits exhibit a remarkable diversity of important horticultural phenotypes. In this study, we initiated a primary quantitative trait loci (QTL) mapping to identify the candidate regions controlling the ovary, fruit, and seed phenotypes. Whole genome sequencing (WGS) was carried out for two differentiated watermelon lines, and 350 Mb (96%) and 354 Mb (97%) of re-sequenced reads covered the reference de novo genome assembly, individually. A total of 45.53% non-synonymous single nucleotide polymorphism (nsSNPs) and 54.47% synonymous SNPs (sSNPs) were spotted, which produced 210 sets of novel SNP-based cleaved amplified polymorphism sequence (CAPS) markers by depicting 46.25% co-dominant polymorphism among parent lines and offspring. A biparental F2:3 mapping population comprised of 100 families was used for trait phenotyping and CAPS genotyping, respectively. The constructed genetic map spanned a total of 2,398.40 centimorgans (cM) in length and averaged 11.42 cM, with 95.99% genome collinearity. A total of 33 QTLs were identified at different genetic positions across the eight chromosomes of watermelon (Chr-01, Chr-02, Chr-04, Chr-05, Chr-06, Chr-07, Chr-10, and Chr-11); among them, eight QTLs of the ovary, sixteen QTLs of the fruit, and nine QTLs of the seed related phenotypes were classified with 5.32–25.99% phenotypic variance explained (PVE). However, twenty-four QTLs were identified as major-effect and nine QTLs were mapped as minor-effect QTLs across the flanking regions of CAPS markers. Some QTLs were exhibited as tightly localized across the nearby genetic regions and explained the pleiotropic effects of multigenic nature. The flanking QTL markers also depicted significant allele specific contributions and accountable genes were predicted for respective traits. Gene Ontology (GO) functional enrichment was categorized in molecular function (MF), cellular components (CC), and biological process (BP); however, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were classified into three main classes of metabolism, genetic information processing, and brite hierarchies. The principal component analysis (PCA) of multivariate phenotypes widely demonstrated the major variability, consistent with the identified QTL regions. In short, we assumed that our identified QTL regions provide valuable genetic insights regarding the watermelon phenotypes and fine genetic mapping could be used to confirm them.

Summary: Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the global coronavirus disease 2019 (COVID-19) pandemic, contains a unique, four amino acid (aa) “PRRA” insertion in the spike (S) protein that creates a transmembrane protease serine 2 (TMPRSS2)/furin cleavage site and enhances viral infectivity. More research into immunogenic epitopes and protective antibodies against this SARS-CoV-2 furin cleavage site is needed. Methods: Combining computational and experimental methods, we identified and characterized an immunogenic epitope overlapping the furin cleavage site that detects antibodies in COVID-19 patients and elicits strong antibody responses in immunized mice. We also identified a high-affinity monoclonal antibody from COVID-19 patient peripheral blood mononuclear cells; the antibody directly binds the furin cleavage site and protects against SARS-CoV-2 infection in a mouse model. Findings: The presence of “PRRA” amino acids in the S protein of SARS-CoV-2 not only creates a furin cleavage site but also generates an immunogenic epitope that elicits an antibody response in COVID-19 patients. An antibody against this epitope protected against SARS-CoV-2 infection in mice. Interpretation: The immunogenic epitope and protective antibody we have identified may augment our strategy in handling COVID-19 epidemic. Funding: The National Natural Science Foundation of China (82102371, 91542201, 81925025, 82073181, and 81802870), the Chinese Academy of Medical Sciences Initiative for Innovative Medicine (2021-I2M-1-047 and 2022-I2M-2-004), the Non-profit Central Research Institute Fund of the Chinese Academy of Medical Sciences (2020-PT310-006, 2019XK310002, and 2018TX31001), the National Key Research and Development Project of China (2020YFC0841700), US National Institute of Health (NIH) funds grant AI158154, University of California Los Angeles (UCLA) AI and Charity Treks, and UCLA DGSOM BSCRC COVID-19 Award Program. H.Y. is supported by Natural Science Foundation of Jiangsu Province (BK20211554 and BE2022728).

Abstract Background Zika virus (ZIKV) infection and ZIKV epidemic have been continuously spreading silently throughout the world and its associated microcephaly and other serious congenital neurological complications poses a significant global threat to public health. Type I interferon response to ZIKV infection in host cells suppresses viral replication by inducing the expression of interferon-stimulated genes (ISGs). Methods The study aims to demonstrate the anti-ZIKV mechanism of PARP11. PARP11 knock out and overexpressing A549 cell lines were constructed to evaluate the anti-ZIKV function of PARP11. PARP11 −/− , PARP12 −/− and PARP11 −/− PARP12 −/− HEK293T cell lines were constructed to explain the synergistic effect of PARP11 and PARP12 on NS1 and NS3 protein degradation. Western blotting, immunofluorescence and immunoprecipitation assay were performed to illustrate the interaction between PARP11 and PARP12. Results Both mRNA and protein levels of PARP11 were induced in WT but not IFNAR1 −/− cells in response to IFNα or IFNβ stimulation and ZIKV infection. ZIKV replication was suppressed in cells expressed PARP11 but was enhanced in PARP11 −/− cells. PARP11 suppressed ZIKV independently on itself PARP enzyme activity. PARP11 interacted with PARP12 and promoted PARP12-mediated ZIKV NS1 and NS3 protein degradation. Conclusion We identified ADP-ribosyltransferase PARP11 as an anti-ZIKV ISG and found that it cooperated with PARP12 to enhance ZIKV NS1 and NS3 protein degradation. Our findings have broadened the understanding of the anti-viral function of ADP-ribosyltransferase family members, and provided potential therapeutic targets against viral ZIKV infection.

Near-surface air temperature (NSAT) is a key parameter in climate changes, environmental ecosystem monitoring, and human settlement issues. As it is difficult for in situ observations to capture the spatial distribution characteristics of NSAT in great detail, various methods have been developed to use remotely sensed land surface temperature and other auxiliary variables to estimate the NSAT. Among them, machine learning turns out to be an exhilarating choice due to its superior performance. However, for long-term dataset estimation, when using machine learning methods with abundant related variables, computation loads and data storage cannot be ignored. Fortunately, Google Earth Engine (GEE) provides a wealth of geospatial datasets and powerful parallel computation capability. In this article, GEE has been utilized to demonstrate the feasibility of estimating long-term 1-km NSAT with two machine-learning models (random forest and deep neural network). After testing the effects of the input variables and the model portability, the 20-year monthly mean 1 km × 1 km NSAT over the Yellow River basin was generated and analyzed. Compared with in situ observations, the overall RMSE, MAE, R2, and R of the NSAT product are 0.429, 0.302, 0.998, and 0.999, respectively. Specifically, for each observation station, R and R2 are greater than 0.997, and RMSE and MAE are smaller than 0.5 and 0.4, respectively. The comparisons with three existing NSAT products show that our product outperforms the other three products. Once again, it is demonstrated in this study that GEE is a powerful platform to generate valuable products with ready-to-use datasets and computation resources.

The Loess Plateau is a typical ecologically sensitive area that can easily be perturbed by the effects of human activities and global climate change. Therefore, it is necessary to develop tools to monitor the environmental quality in the LP quickly and accurately. To reveal the spatio-temporal changes in environmental quality in the LP from 2000 to 2020, we used the Moderate-Resolution Imaging Spectroradiometer (MODIS) products on the Google Earth Engine platform and constructed the remote sensing ecological index (RSEI) through principal component analysis (PCA). Then, Sen–Mann–Kendall methods were applied to determine the changing trend of the environmental quality of the LP. Finally, natural and anthropogenic factors affecting the environmental quality were probed using a geographical detector model. The results showed that: (1) the average RSEI values in 2000, 2010 and 2020 were 0.396, 0.468 and 0.511, respectively, displaying an upward trend from 2000 to 2020, with a growth rate of 0.005 year−1. The overall environment quality was moderate (0.4–0.6). (2) In terms of spatial distribution, the environmental quality was excellent in the southeast and poor in the northwest of the LP. The areas with improved environmental quality (84.51%) were located in all the counties, whereas the areas with degraded environmental quality (8.11%) occurred in the north and southeast of the study area. (3) Greenness, heat, wetness, dryness and land use types were prominent factors affecting RSEI throughout the study period; additionally, the total industrial gross domestic product showed a growing influence. The contribution of multi-factor interaction was stronger than that of single factors. The results will provide a reference and a new research perspective for local environmental protection and regional planning.

Abstract Circulating tumour DNA (ctDNA) detection and monitoring have enormous potential clinical utility in oncology. We describe here a fast, flexible and cost-effective method to profile multiple genes simultaneously in low input cell-free DNA (cfDNA): Next Generation-Targeted Amplicon Sequencing (NG-TAS). We designed a panel of 377 amplicons spanning 20 cancer genes and tested the NG-TAS pipeline using cell-free DNA from two HapMap lymphoblastoid cell lines. NG-TAS consistently detected mutations in cfDNA when mutation allele fraction was > 1%. We applied NG-TAS to a clinical cohort of metastatic breast cancer patients, demonstrating its potential in monitoring the disease. The computational pipeline is available at https://github.com/cclab-brca/NGTAS_pipeline.

Anthocyanins are among the most important factors affecting the leaf colour of kale, and MYB proteins are key transcription factors regulating their synthesis in plants. In this study, purple-leaf kale ‘D07’ was used as a test material, and the complete coding sequence of BoMYB was determined by homologous cloning. Bioinformatics analysis showed that the cDNA sequence of the BoMYB coding region was 753 base pairs in length and encoded a predicted 250-amino acid protein with a mass of 25 kDa and an isoelectric point of 9.08. The BoMYB protein was predicted to contain two MYB conserved domains and to be localized in the cell nucleus. A phylogenetic tree indicated that the amino acid sequence encoded by BoMYB in kale was most closely related to the MYB protein sequence of Brassica napus. The expression patterns of BoMYB were evaluated in different tissues of ‘D07’ by quantitative real-time polymerase chain reaction, and the results showed that BoMYB was expressed in kale roots, stems, inner leaves, and outer leaves. However, the expression levels were tissue specific and correlated with the anthocyanin content in each tissue. To confirm the effect of BoMYB on anthocyanin synthesis and accumulation, ectopic expression in Arabidopsis was performed. Morphological observation showed that overexpression of BoMYB increased the accumulation of anthocyanidins in transgenic Arabidopsis. Thus, BoMYB may encode an MYB transcription factor, which positively regulates the synthesis of anthocyanins in kale.

The widespread prevalence of coronavirus disease-2019 (COVID-19) which is caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, has resulted in a severe global public health emergency. However, there are no sensitive biomarkers to predict the disease prognosis of COVID-19 patients. Here, we have identified interleukin-8 (IL-8) as a biomarker candidate to predict different disease severity and prognosis of COVID-19 patients. While serum IL-6 become obviously elevated in severe COVID-19 patients, serum IL-8 was easily detectible in COVID-19 patients with mild syndromes. Furthermore, lL-8 levels correlated better than IL-6 levels with the overall clinical disease scores at different stages of the same COVID-19 patients. Thus, our studies suggest that IL-6 and IL-8 can be respectively used as biomarkers for severe COVID-19 patients and for COVID-19 disease prognosis.

Specific surface area and active groups are major concerns in the design and synthesis of metal ion adsorbent. Inspired by coral's high efficiency in preying on tiny plankton in the ocean, we pioneered a simple method for the in situ construction of “nano-tentacles” based on the original porous material skeleton. The introduction of “nano-tentacles” can further redesign and remolding of the existing interconnected pores to increase the specific surface areas and specific chelating sites for target metal ions. Herein, a proof-of-concept design is illustrated by in situ growing (3-aminopropyl)trimethoxysilane (APS) on the inner wall of the porous structure of chitosan/graphene oxide composite gel (CGG). The resulting material (NT-CGG) has a distribution coefficient (Kd) of 1.25 × 108 mL g−1, which exhibits ultrahigh affinity for lead ions, and the uptake capacity can reach 470 mg g−1. More significantly, the NT-CGG can effectively remove lead from 10 ppm to undetectable levels (≤0.02 ppb) with remove efficiency ≥99.9998% in the breakthrough experiment. The method proposed in this paper may be widely applicable to the redesign and remolding of most existing porous materials.

Cucurbits (Cucurbitaceae family) include many economically important fruit vegetable crops such as watermelon, pumpkin/squash, cucumber, and melon. Seed size (SS) is an important trait in cucurbits breeding, which is controlled by quantitative trait loci (QTL). Recent advances have deciphered several signaling pathways underlying seed size variation in model plants such as Arabidopsis and rice, but little is known on the genetic basis of SS variation in cucurbits. Here we conducted literature review on seed size QTL identified in watermelon, pumpkin/squash, cucumber and melon, and inferred 14, 9 and 13 consensus SS QTL based on their physical positions in respective draft genomes. Among them, four from watermelon (ClSS2.2, ClSS6.1, ClSS6.2, and ClSS8.2), two from cucumber (CsSS4.1 and CsSS5.1), and one from melon (CmSS11.1) were major-effect, stable QTL for seed size and weight. Whole genome sequence alignment revealed that these major-effect QTL were located in syntenic regions across different genomes suggesting possible structural and functional conservation of some important genes for seed size control in cucurbit crops. Annotation of genes in the four watermelon consensus SS QTL regions identified genes that are known to play important roles in seed size control including members of the zinc finger protein and the E3 ubiquitin-protein ligase families. The present work highlights the utility of comparative analysis in understanding the genetic basis of seed size variation, which may help future mapping and cloning of seed size QTL in cucurbits.

With the rapid process of urbanization, the urban heat island (UHI), the phenomenon where urban regions become hotter than their surroundings, is increasingly aggravated. The UHI is affected by multiple factors overall. However, it is difficult to dissociate the effect of one aspect by widely used approaches such as the remote-sensing-based method. To qualify the response of surface UHI to the land use and land cover (LULC) changes, this study took the numerical land model named u-HRLDAS (urbanized high-resolution land data assimilation system) as the modeling tool to investigate the effect of LULC changes on the UHI from 1980 to 2013 in Wuhan city, China. Firstly, the simulation accuracy of the model was improved, and the summer urban heat environment was simulated for the summer of 2013. Secondly, taking the simulation in 2013 as the control case (CNTL), the LULC in 1980, 1990, and 2000 were replaced by the LULC while the other conditions kept the same as the CNTL to explore the effect of LULC on UHI. The results indicate that the proper configuration of the modeling setup and accurate surface input data are considered important for the simulated results of the u-HRLDAS. The response intensity of UHI to LULC changes after 2000 was stronger than that of before 2000. From the spatial perspective, the part that had the strongest response intensity of land surface temperature to LULC changes was the region between the third ring road and the inner ring road of Wuhan. This study can provide a reference for cognizing the urban heat environment and guide policy making for urban development.

Low-cost air quality sensors (LCSs) have become more widespread due to their low cost and increased capabilities; however, to supplement more traditional air quality networks, the performance of these LCSs needs to be validated. This study focused on NO2 measurements from eight Clarity Node-S sensors and used various environmental factors to calibrate the LCSs. To validate the calibration performance, we calculated the root-mean-square error (RMSE), mean absolute error (MAE), R2, and slope compared to reference measurements. Raw results from six of these sensors were comparable to those reported for other NO2 LCSs; however, two of the evaluated LCSs had RMSE values ~20 ppb higher than the other six LCSs. By applying a sensor-specific calibration that corrects for relative humidity, temperature, and ozone, this discrepancy was mitigated. In addition, this calibration improved the RMSE, MAE, R2, and slope of all eight LCS compared to the raw data. It should be noted that relatively stable environmental conditions over the course of the LCS deployment period benefited calibration performance over time. These results demonstrate the importance of developing LCS calibration models for individual sensors that consider pertinent environmental factors.

Sixteen new prenylated flavonoids, sinoflavonoids P−Z (1−11) and sinoflavonoids NA−NE (12−16), were isolated from the fruit of Sinopodophyllum hexandrum, along with eight known analogues (17−24). Their structures were elucidated on the basis of extensive spectroscopic data (HR-ESI-MS, 1H-NMR, 13C-NMR, HSQC, HMBC). The cytotoxic activities of compounds 1−18, 20, and 22 were evaluated by MTT assay. Compound 6 showed the most potent cytotoxicity in MCF-7, and HepG2 cell lines, with IC50 values of 6.25 and 3.83 μM, respectively.

Six new coumarin glycosides, genglycoside A–F (1–6), were isolated from the aerial parts of Gendarussa vulgaris, along with ten known analogues (7–16). Their structures were unambiguously established on the basis of extensive spectroscopic data and HPLC analysis. The cytotoxic activities of all isolated compounds were evaluated by MTT assay. Compound 12 showed the most potent cytotoxicity in Eca-109, MCF-7, and HepG2 cell lines. By the preliminary structure–activity relationships, it was firstly discovered that the glycosylation or esterification at 7,8-dihydroxy or 7-hydroxy drastically reduced the cytotoxic activity of the parent coumarin.

Nine new gingerols, including three 6-oxo-shogaol derivatives [(Z)-6-oxo-[6]-shogaol (1), (Z)-6-oxo-[8]-shogaol (2), (Z)-6-oxo-[10]-shogaol (3)], one 6-oxoparadol derivative [6-oxo-[6]-paradol (4)], one isoshogaol derivative [(E)-[4]-isoshogaol (5)], and four paradoldiene derivatives [(4E,6Z)-[4]-paradoldiene (8), (4E,6E)-[6]-paradoldiene (9), (4E,6E)-[8]-paradoldiene (10), (4E,6Z)-[8]-paradoldiene (11)], together with eight known analogues, were isolated from the rhizoma of Zingiber officinale. Their structures were elucidated on the basis of spectroscopic data. It was noted that the isolation of 6-oxo-shogaol derivatives represents the first report of gingerols containing one 1,4-enedione motif. Their structures were elucidated on the basis of spectroscopic and HRESIMS data. All the new compounds were evaluated for their cytotoxic activities against human cancer cells (MCF-7, HepG-2, KYSE-150).

Leaf spot disease caused by the fungus Fusarium proliferatum (Matsushima) Nirenberg is a destructive disease of tomato plants in China. Typical symptoms of infected tomato plants are softened and wilted stems and leaves, leading to the eventual death of the entire plant. In this study, we resorted to transcriptional profile analysis to gain insight into the repertoire of effectors involved in F. proliferatum–tomato interactions. A total of 61,544,598 clean reads were de novo assembled to provide a F. proliferatum reference transcriptome. From these, 75,044 unigenes were obtained, with 19.46% of the unigenes being assigned to 276 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, with 22.3% having a homology with genes from F. fujikuroi. A total of 18,075 differentially expressed genes (DEGs) were identified, 720 of which were found to code for secreted proteins. Of these, 184 were identified as candidate effectors, while 79.89% had an upregulated expression. Moreover, 17 genes that were differentially expressed in RNA-seq studies were randomly selected for validation by quantitative real-time polymerase chain reaction (qRT–PCR). The study demonstrates that transcriptome analysis could be an effective method for identifying the repertoire of candidate effectors and may provide an invaluable resource for future functional analyses of F. proliferatum pathogenicity in F. proliferatum and tomato plant–host interactions.