室内植物表型平台及性状鉴定研究进展和展望

Plant phenomics is under rapid development in recent years, a research field that is progressing towards integration, scalability, multi-perceptivity and high-throughput analysis. Through combining remote sensing, Internet of Things (IoT), robotics, computer vision, and artificial intelligence techniques such as machine learning and deep learning, relevant research methodologies, biological applications and theoretical foundation of this research domain have been advancing speedily in recent years. This article first introduces the current trends of plant phenomics and its related progress in China and worldwide. Then, it focuses on discussing the characteristics of indoor phenotyping and phenotypic traits that are suitable for indoor experiments, including yield, quality, and stress related traits such as drought, cold and heat resistance, salt stress, heavy metals, and pests. By connecting key phenotypic traits with important biological questions in yield production, crop quality and Stress-related tolerance, we associated indoor phenotyping hardware with relevant biological applications and their plant model systems, for which a range of indoor phenotyping devices and platforms are listed and categorised according to their throughput, sensor integration, platform size, and applications. Additionally, this article introduces existing data management solutions and analysis software packages that are representative for phenotypic analysis. For example, ISA-Tab and MIAPPE ontology standards for capturing metadata in plant phenotyping experiments, PHIS and CropSight for managing complicated datasets, and Python or MATLAB programming languages for automated image analysis based on libraries such as OpenCV, Scikit-Image, MATLAB Image Processing Toolbox. Finally, due to the importance of extracting meaningful information from big phenotyping datasets, this article pays extra attention to the future development of plant phenomics in China, with suggestions and recommendations for the integration of multi-scale phenotyping data to increase confidence in research outcomes, the cultivation of cross-disciplinary researchers to lead the next-generation plant research, as well as the collaboration between academia and industry to enable world-leading research activities in the near future

Synergistic up-regulation of CXCL10 by virus and IFN γ in human airway epithelial cells.

Airway epithelial cells are the first line of defense against viral infections and are instrumental in coordinating the inflammatory response. In this study, we demonstrate the synergistic stimulation of CXCL10 mRNA and protein, a key chemokine responsible for the early immune response to viral infection, following treatment of airway epithelial cells with IFN γ and influenza virus. The synergism also occurred when the cells were treated with IFN γ and a viral replication mimicker (dsRNA) both in vitro and in vivo. Despite the requirement of type I interferon (IFNAR) signaling in dsRNA-induced CXCL10, the synergism was independent of the IFNAR pathway since it wasn't affected by the addition of a neutralizing IFNAR antibody or the complete lack of IFNAR expression. Furthermore, the same synergistic effect was also observed when a CXCL10 promoter reporter was examined. Although the responsive promoter region contains both ISRE and NFκB sites, western blot analysis indicated that the combined treatment of IFN γ and dsRNA significantly augmented NFκB but not STAT1 activation as compared to the single treatment. Therefore, we conclude that IFN γ and dsRNA act in concert to potentiate CXCL10 expression in airway epithelial cells via an NFκB-dependent but IFNAR-STAT independent pathway and it is at least partly regulated at the transcriptional level

Cloning and Characterization of Human MUC19 Gene

The most recently discovered gel-forming mucin, MUC19, is expressed in both salivary glands and tracheal submucosal glands. We previously cloned the 3′−end partial sequence ({"type":"entrez-nucleotide","attrs":{"text":"AY236870","term_id":"32395927","term_text":"AY236870"}}AY236870), and here report the complete sequencing of the entire MUC19 cDNA. One highly variable region (HVR) was discovered in the 5′ end of MUC19. A total of 20 different splicing variants were detected in HVR, and 18 variants are able to translate into proteins along with the rest of the MUC19 sequence. The longest variant of MUC19 consists of 182 exons, with a transcript of approximately 25 kb. A central exon of approximately 12 kb contains highly repetitive sequences and has no intron interruption. The deduced MUC19 protein has the bona fide gel-forming mucin structure, VWD-VWD-VWD-“threonine/serine-rich repeats”-VWC-CT. An unusual structural feature of MUC19, which is lacking in other gel-forming mucins, is its long amino terminus upstream of the first VWD domain. The long amino terminus is mostly translated from the sequences in HVR, and contains serine-rich repetitive sequences. To validate the integrity of the MUC19 sequence, primers from both the 3′ and 5′ end were used to demonstrate a similar tissue expression pattern of MUC19 in trachea and salivary glands. In addition, antibodies were developed against either the amino (N) or carboxy (C) terminus of MUC19, and similar antibody staining patterns were observed in both salivary and tracheal submucosal glands. In conclusion, we have cloned and elucidated the entire MUC19 gene, which will facilitate understanding of the function and regulation of this important, yet understudied, mucin gene in airway diseases

Quali regole per la sharing mobility in Europa. Un\u2019introduzione

All over Europe urban mobility services are subject to specialized regulatory regimes. In the last decade, new technologies have upended the sector, making possible new ways of organizing the industry. Platforms like Uber and Lyft have been among the first to seize these possibilities. However, they have often done so without regard for national and local laws. In response to these changes many EU jurisdictions have amended their sectoral regulations, revisiting issues such as licensing, background checks and insurance. The result has been a vast landscape of legal, commercial, and political conflict where local administrators, private operators and citizens are obliged to act within a normative chaos. Sharing mobility is facing a major challenge in Europe. In its landmark judgment in December 2017, the European Court of Justice concluded that platforms such as Uber is \u2018a service in the field of transport\u2019 that are excluded from the scope of the Freedom to provide services, the Directive on services and the Directive on e-commerce. It follows that it is for the Member States and local authorities to regulate the conditions under which such services are to be provided (Case C-434/15). Yet, EU law is deeply involved in the regulation of such services. The surrounding legal framework for sharing mobility includes not only competition, labor law and consumer protection, but it also deeply affects social inclusion, environmental sustainability and urban planning, among others. For these reasons, the central question for the European Union regards the appropriate site of authority in multi-level systems. This Special Issue has been conceived within the framework of the Jean Monnet Project RIDER: an innovative project that combines research and teaching to offer a "new product" with a clear idea: \u201cfrom the Academic world to Civil society\u201d. The aim is to offer real support to the public administrator in the creation of new policies and rules for sharing mobility and in following those good practices that will be developed during the lifetime of the project, taking into account the many dimensions involved: urban impact, social inclusion, environment, and so on

Construction of a one-step multiplex real-time PCR assay for the detection of serogroups A, B, and E of Pasteurella multocida associated with bovine pasteurellosis

Bovine pasteurellosis, caused by serogroups A, B, and E of Pasteurella multocida (Pm), is mainly manifested as bovine respiratory disease (BRD) and hemorrhagic septicemia (HS). The disease has caused a great economic loss for the cattle industry globally. Therefore, identifying the Pm serogroups is critical for optimal diagnosis and subsequent clinical treatment and even epidemiological studies. In this study, a one-step multiplex real-time PCR assay was established. Three pairs of specific primers were prepared to detect the highly conserved genomic regions of serogroups A (HyaD), B (bcbD), and E (ecbJ) of Pm, respectively. The results depicted that the method had no cross-reaction with other bovine pathogens (Mannheimia hemolytica, Escherichia coli, Listeria monocytogenes, Staphylococcus aureus, Salmonella Dublin, Mycobacterium paratuberculosis, infectious bovine rhinotracheitis virus, and Mycoplasma bovis). The linear range (107 to 102 copies/μL) showed the R2 values for serogroups A, B, and E of Pm as 0.9975, 0.9964, and 0.996, respectively. The multiplex real-time PCR efficiency was 90.30%, 90.72%, and 90.57% for CartA, CartB, and CartE, respectively. The sensitivity result showed that the serogroups A, B, and E of Pm could be detected to be as low as 10 copies/μL. The repeatability result clarified that an intra-assay and an inter-assay coefficient of variation of serogroups A, B, and E of Pm was < 2%. For the clinical samples, the detection rate was higher than the OIE-recommended ordinary PCR. Overall, the established one-step multiplex real-time PCR assay may be a valuable tool for the rapid and early detection of the serogroups A, B, and E of Pm with high specificity and sensitivity

The Role of FGFR1 Gene Amplification as a Poor Prognostic Factor in Squamous Cell Lung Cancer: A Meta-Analysis of Published Data

Objectives. The prognostic factors of the fibroblast growth factor receptor 1 (FGFR1) in non-small cell lung cancer (NSCLC) remain controversial. Methods. We conducted a meta-analysis of published studies from 1974 to February 2015. In absence of quality difference between studies of reporting significant and nonsignificant results, the relationship between FGFR1 amplification and clinicopathological parameters in NSCLC was analyzed. And also the combined hazard ratio (HR) and their corresponding 95% confidence interval (CI) were calculated in terms of overall survival. Results. 3178 patients (12 studies) were included in the analysis. It was shown that FGFR1 amplification was significantly more prevalent among male patients (RR 2.03, 95% CI 1.57-2.63) with squamous cell lung cancer (SQCC) (RR 3.49, 95% CI 2.62-4.64) and current smokers (RR 2.63, 95% CI 1.92-3.60). The pooled data also showed that the FGFR1 amplification was a poor prognostic factor in SQCC (HR 1.38, 95% CI 1.07-1.78), Asian patients (HR 1.78, 95% CI 1.22-2.60), and fluorescence in situ hybridization (FISH) method (HR 1.30, 95% CI 1.06-1.58). Conclusions. This meta-analysis strongly suggests that FGFR1 amplification occurs more frequently in male, SQCC and smokers, and it is a risk factor for poor prognosis among Asian patients with SQCC

Natural Coevolution of Tumor and Immunoenvironment in Glioblastoma.

Isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) has a dismal prognosis. A better understanding of tumor evolution holds the key to developing more effective treatment. Here we study GBM\u27s natural evolutionary trajectory by using rare multifocal samples. We sequenced 61,062 single cells from eight multifocal IDH wild-type primary GBMs and defined a natural evolution signature (NES) of the tumor. We show that the NES significantly associates with the activation of transcription factors that regulate brain development, including MYBL2 and FOSL2. Hypoxia is involved in inducing NES transition potentially via activation of the HIF1A-FOSL2 axis. High-NES tumor cells could recruit and polarize bone marrow-derived macrophages through activation of the FOSL2-ANXA1-FPR1/3 axis. These polarized macrophages can efficiently suppress T-cell activity and accelerate NES transition in tumor cells. Moreover, the polarized macrophages could upregulate CCL2 to induce tumor cell migration. SIGNIFICANCE: GBM progression could be induced by hypoxia via the HIF1A-FOSL2 axis. Tumor-derived ANXA1 is associated with recruitment and polarization of bone marrow-derived macrophages to suppress the immunoenvironment. The polarized macrophages promote tumor cell NES transition and migration. This article is highlighted in the In This Issue feature, p. 2711

Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition

Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. Fellowship under Grant PD/BD/137401/2018. Team YAI (Track 3) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 109-2221-E-197-026. Team Indora (Track 3) was supported in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovakia, under Grant 1/0177/21, and in part by the Slovak Research and Development Agency under Contract APVV-15-0091. Team TJU (Track 3) was supported in part by the National Natural Science Foundation of China under Grant 61771338 and in part by the Tianjin Research Funding under Grant 18ZXRHSY00190. Team Next-Newbie Reckoners (Track 3) were supported by the Singapore Government through the Industry Alignment Fund—Industry Collaboration Projects Grant. This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU). Team KawaguchiLab (Track 5) was supported by JSPS KAKENHI under Grant JP17H01762. Team WHU&AutoNavi (Track 6) was supported by the National Key Research and Development Program of China under Grant 2016YFB0502202. Team YAI (Tracks 6 and 7) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 110-2634-F-155-001

Off-Line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences From IPIN 2020 Competition

Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. Fellowship under Grant PD/BD/137401/2018. Team YAI (Track 3) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 109-2221-E-197-026. Team Indora (Track 3) was supported in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovakia, under Grant 1/0177/21, and in part by the Slovak Research and Development Agency under Contract APVV-15-0091. Team TJU (Track 3) was supported in part by the National Natural Science Foundation of China under Grant 61771338 and in part by the Tianjin Research Funding under Grant 18ZXRHSY00190. Team Next-Newbie Reckoners (Track 3) were supported by the Singapore Government through the Industry Alignment Fund—Industry Collaboration Projects Grant. This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU). Team KawaguchiLab (Track 5) was supported by JSPS KAKENHI under Grant JP17H01762. Team WHU&AutoNavi (Track 6) was supported by the National Key Research and Development Program of China under Grant 2016YFB0502202. Team YAI (Tracks 6 and 7) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 110-2634-F-155-001.Peer reviewe