Diversity, prevalence, and expression of cyanase genes (cynS) in planktonic marine microorganisms

Cyanate is utilized by many microbes as an organic nitrogen source. The key enzyme for cyanate metabolism is cyanase, converting cyanate to ammonium and carbon dioxide. Although the cyanase gene cynS has been identified in many species, the diversity, prevalence, and expression of cynS in marine microbial communities remains poorly understood. Here, based on the full-length cDNA sequence of a dinoflagellate cynS and 260 homologs across the tree of life, we extend the conserved nature of cyanases by the identification of additional ultra-conserved residues as part of the modeled holoenzyme structure. Our phylogenetic analysis showed that horizontal gene transfer of cynS appears to be more prominent than previously reported for bacteria, archaea, chlorophytes, and metazoans. Quantitative analyses of marine planktonic metagenomes revealed that cynS is as prevalent as ureC (urease subunit alpha), suggesting that cyanate plays an important role in nitrogen metabolism of marine microbes. Highly abundant cynS transcripts from phytoplankton and nitrite-oxidizing bacteria identified in global ocean metatranscriptomes indicate that cyanases potentially occupy a key position in the marine nitrogen cycle by facilitating photosynthetic assimilation of organic N and its remineralisation to NO3 by the activity of nitrifying bacteria

The Potential Role of ORM2 in the Development of Colorectal Cancer

Colorectal cancer (CRC) is the third most common malignancy in the world. The risk of death is closely correlated to the stage of CRC at the time of primary diagnosis. Therefore, there is a compelling need for the identification of blood biomarkers that can enable early detection of CRC. We used a quantitative proteomic approach with isobaric labeling (iTRAQ) to examine changes in the plasma proteome of 10 patients with CRC compared to healthy volunteers. Enzyme-Linked Immunosorbnent Assay (ELISA) and Western blot were used for further validation. In our quantitative proteomics analysis, we detected 75 human plasma proteins with more than 95% confidence using iTRAQ labeling in conjunction with microQ-TOF MS. 9 up-regulated and 4 down-regulated proteins were observed in the CRC group. The ORM2 level in plasma was confirmed to be significantly elevated in patients suffering from CRC compared with the controls. ORM2 expression in CRC tissues was significantly increased compared with that in corresponding adjacent normal mucous tissues (P<0.001). ITRAQ together with Q-TOF/MS is a sensitive and reproducible technique of quantitative proteomics. Alteration in expression of ORM2 suggests that ORM2 could be used as a potential biomarker in the diagnosis of CRC

Ticagrelor vs Clopidogrel in CYP2C19 loss-of-function carriers with Stroke or TIA

BACKGROUNDComparisons between ticagrelor- aspirin and clopidogrel-aspirin in CYP2C19 loss-of-function carriers have not been well studied for secondary stroke prevention.METHODSWe conducted a randomized, double-blind, placebo-controlled trial of 6,412 patients with a minor ischemic stroke or TIA who carried CYP2C19 LOF alleles determined by point-of-care testing. Patients were randomly assigned within 24 hours after symptom onset, in a 1:1 ratio to receive ticagrelor (180 mg loading dose on day 1 followed by 90 mg twice daily for days 2 through 90) or clopidogrel (300 mg loading dose on day 1 followed by 75 mg per day for days 2 through 90), plus aspirin (75-300 mg loading dose followed by 75 mg daily for 21 days). The primary efficacy outcome was stroke and the primary safety outcome was severe or moderate bleeding, both within 90 days. RESULTSStroke occurred within 90 days in 191 (6.0%) versus 243 (7.6%), respectively (hazard ratio, 0.77; 95% confidence interval, 0.64 to 0.94; P=0.008). Moderate or severe bleeding occurred in 9 patients (0.3%) in the ticagrelor-aspirin group and in 11 patients (0.3%) in the clopidogrel-aspirin group; any bleeding event occurred in 170 patients (5.3%) vs 80 (2.5%), respectively. CONCLUSIONSAmong Chinese patients with minor ischemic stroke or TIA within 24 hours after symptoms onset who were carriers of CYP2C19 loss-of-function alleles, ticagrelor- aspirin was modestly better than clopidogrel-aspirin for reducing the risk of stroke but was associated with more total bleeding events at 90 days. (CHANCE-2 ClinicalTrials.gov number, NCT04078737.

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

HPV prevalence and genotype distribution among women in eastern China during the Covid-19 pandemic

Since March 2020, the pandemic caused by SARS-CoV-2 has affected nearly all aspects of daily life. In this study, we investigated the age-stratified prevalence and genotype distribution of human papillomavirus (HPV) among females in Shandong province (eastern China) and aimed to provide guidance on HPV-based cervical cancer screening and vaccination. The distribution of HPV genotypes was analyzed using PCR-Reverse Dot Hybridization. The overall infection rate of HPV was 16.4%, which was dominated by high-risk genotypes. The most prevalent genotype was HPV16 (2.9%), followed by HPV52 (2.3%), HPV53 (1.8%), HPV58 (1.5%), and HPV51 (1.3%). Among the positive cases with HPV infection, single-genotype infection was significantly higher than that of multi-genotype infection. In subgroup analyses by age (≤25, 26–35, 36–45, 46–55, >55), HPV16, 52, and 53 were consistently the three most common hrHPV genotypes in all age groups. The infection rate of multi-genotypes in the ≤25 and >55 age groups was significantly higher than that in other age groups. A bimodal distribution of HPV infection rate was observed in different age groups. Among lrHPV genotypes, HPV6, HPV11, and HPV81 were the three most common types in the ≤25 age group, while in other age groups, HPV81, HPV42, and HPV43 are the three most common lrHPV genotypes. This study provides basic information on the distribution and genotypes of HPV in the female population in eastern China, which could improve the application of HPV diagnostic probes and vaccines

Evaluation of the Simulation of Typhoon Lekima (2019) Based on Different Physical Parameterization Schemes and FY-3D Satellite’s MWHS-2 Data Assimilation

In this study, the case of super typhoon Lekima, which landed in Jiangsu and Zhejiang Province on 4 August 2019, is numerically simulated. Based on the Weather Research and Forecasting (WRF) model, the sensitivity experiments are carried out with different combinations of physical parameterization schemes. The results show that microphysical schemes have obvious impacts on the simulation of the typhoon’s track, while the intensity of the simulated typhoon is more sensitive to surface physical schemes. Based on the results of the typhoon’s track and intensity simulation, one parameterization scheme was further selected to provide the background field for the following data assimilation experiments. Using the three-dimensional variational (3DVar) data assimilation method, the Microwave Humidity Sounder-2 (MWHS-2) radiance data onboard the Fengyun-3D satellite (FY-3D) were assimilated for this case. It was found that the assimilation of the FY-3D MWHS-2 radiance data was able to optimize the initial field of the numerical model in terms of the model variables, especially for the humidity. Finally, by the inspection of the typhoon’s track and intensity forecast, it was found that the assimilation of FY-3D MWHS-2 radiance data improved the skill of the prediction for both the typhoon’s track and intensity

Evaluation of the Simulation of Typhoon Lekima (2019) Based on Different Physical Parameterization Schemes and FY-3D Satellite’s MWHS-2 Data Assimilation

In this study, the case of super typhoon Lekima, which landed in Jiangsu and Zhejiang Province on 4 August 2019, is numerically simulated. Based on the Weather Research and Forecasting (WRF) model, the sensitivity experiments are carried out with different combinations of physical parameterization schemes. The results show that microphysical schemes have obvious impacts on the simulation of the typhoon’s track, while the intensity of the simulated typhoon is more sensitive to surface physical schemes. Based on the results of the typhoon’s track and intensity simulation, one parameterization scheme was further selected to provide the background field for the following data assimilation experiments. Using the three-dimensional variational (3DVar) data assimilation method, the Microwave Humidity Sounder-2 (MWHS-2) radiance data onboard the Fengyun-3D satellite (FY-3D) were assimilated for this case. It was found that the assimilation of the FY-3D MWHS-2 radiance data was able to optimize the initial field of the numerical model in terms of the model variables, especially for the humidity. Finally, by the inspection of the typhoon’s track and intensity forecast, it was found that the assimilation of FY-3D MWHS-2 radiance data improved the skill of the prediction for both the typhoon’s track and intensity

Detection of Chromosomal Segments Introgressed from Wild Species of Carrot into Cultivars: Quantitative Trait Loci Mapping for Morphological Features in Backcross Inbred Lines

Cultivated carrot is thought to have been domesticated from a wild species, and various phenotypes developed through human domestication and selection over the past several centuries. Little is known about the genomic contribution of wild species to the phenotypes of present-day cultivars, although several studies have focused on identifying genetic loci that contribute to the morphology of storage roots. A backcross inbred line (BIL) population derived from a cross between the wild species Daucus carota ssp. carota “Songzi” and the orange cultivar “Amsterdam forcing” was developed. The morphological features in the BIL population became more diverse after several generations of selfing BC2F1 plants. Only few lines retained features of wild parent. Genomic resequencing of the two parental lines and the BILs resulted in 3,223,651 single nucleotide polymorphisms (SNPs), and 13,445 bin markers were generated using a sliding window approach. We constructed a genetic map with 2027 bins containing 154,776 SNPs; the total genetic distance was 1436.43 cM and the average interval between the bins was 0.71 cm. Five stable QTLs related to root length, root shoulder width, dry material content of root, and ratio of root shoulder width to root middle width were consistently detected on chromosome 2 in both years and explained 23.4–66.9% of the phenotypic variance. The effects of introgressed genomic segments from the wild species on the storage root are reported and will enable the identification of functional genes that control root morphological traits in carrot

An Approach for Rice Bacterial Leaf Streak Disease Segmentation and Disease Severity Estimation

Rice bacterial leaf streak (BLS) is a serious disease in rice leaves and can seriously affect the quality and quantity of rice growth. Automatic estimation of disease severity is a crucial requirement in agricultural production. To address this, a new method (termed BLSNet) was proposed for rice and BLS leaf lesion recognition and segmentation based on a UNet network in semantic segmentation. An attention mechanism and multi-scale extraction integration were used in BLSNet to improve the accuracy of lesion segmentation. We compared the performance of the proposed network with that of DeepLabv3+ and UNet as benchmark models used in semantic segmentation. It was found that the proposed BLSNet model demonstrated higher segmentation and class accuracy. A preliminary investigation of BLS disease severity estimation was carried out based on our BLS segmentation results, and it was found that the proposed BLSNet method has strong potential to be a reliable automatic estimator of BLS disease severity