Technology generation to dissemination:lessons learned from the tef improvement project

Indigenous crops also known as orphan crops are key contributors to food security, which is becoming increasingly vulnerable with the current trend of population growth and climate change. They have the major advantage that they fit well into the general socio-economic and ecological context of developing world agriculture. However, most indigenous crops did not benefit from the Green Revolution, which dramatically increased the yield of major crops such as wheat and rice. Here, we describe the Tef Improvement Project, which employs both conventional- and molecular-breeding techniques to improve tef\u2014an orphan crop important to the food security in the Horn of Africa, a region of the world with recurring devastating famines. We have established an efficient pipeline to bring improved tef lines from the laboratory to the farmers of Ethiopia. Of critical importance to the long-term success of this project is the cooperation among participants in Ethiopia and Switzerland, including donors, policy makers, research institutions, and farmers. Together, European and African scientists have developed a pipeline using breeding and genomic tools to improve the orphan crop tef and bring new cultivars to the farmers in Ethiopia. We highlight a new variety, Tesfa, developed in this pipeline and possessing a novel and desirable combination of traits. Tesfa\u2019s recent approval for release illustrates the success of the project and marks a milestone as it is the first variety (of many in the pipeline) to be released

CT-based radiomic phenotypes of lung adenocarcinoma: a preliminary comparative analysis with targeted next-generation sequencing

ObjectivesThis study aimed to explore the relationship between computed tomography (CT)-based radiomic phenotypes and genomic profiles, including expression of programmed cell death-ligand 1 (PD-L1) and the 10 major genes, such as epidermal growth factor receptor (EGFR), tumor protein 53 (TP53), and Kirsten rat sarcoma viral oncogene (KRAS), in patients with lung adenocarcinoma (LUAD).MethodsIn total, 288 consecutive patients with pathologically confirmed LUAD were enrolled in this retrospective study. Radiomic features were extracted from preoperative CT images, and targeted genomic data were profiled through next-generation sequencing. PD-L1 expression was assessed by immunohistochemistry staining (chi-square test or Fisher's exact test for categorical data and the Kruskal–Wallis test for continuous data). A total of 1,013 radiomic features were obtained from each patient's CT images. Consensus clustering was used to cluster patients on the basis of radiomic features.ResultsThe 288 patients were classified according to consensus clustering into four radiomic phenotypes: Cluster 1 (n = 11) involving mainly large solid masses with a maximum diameter of 5.1 ± 2.0 cm; Clusters 2 and 3 involving mainly part-solid and solid masses with maximum diameters of 2.1 ± 1.4 cm and 2.1 ± 0.9 cm, respectively; and Cluster 4 involving mostly small ground-glass opacity lesions with a maximum diameter of 1.0 ± 0.9 cm. Differences in maximum diameter, PD-L1 expression, and TP53, EGFR, BRAF, ROS1, and ERBB2 mutations among the four clusters were statistically significant. Regarding targeted therapy and immunotherapy, EGFR mutations were highest in Cluster 2 (73.1%); PD-L1 expression was highest in Cluster 1 (45.5%).ConclusionOur findings provide evidence that CT-based radiomic phenotypes could non-invasively identify LUADs with different molecular characteristics, showing the potential to provide personalized treatment decision-making support for LUAD patients

Inonotus sanghuang Polyphenols Attenuate Inflammatory Response Via Modulating the Crosstalk Between Macrophages and Adipocytes

Aims: Obesity is characterized as a chronic state of low-grade inflammation with progressive immune cell infiltration into adipose tissue. Adipose tissue macrophages play a critical role in the establishment of chronic inflammatory states and metabolic dysfunctions. Inonotus (I.) sanghuang and its extract polyphenols exhibit anti-carcinogenesis, anti-inflammatory, and anti-oxidant activities. However, the action of I. sanghuang polyphenols in obesity-related inflammation has not been reported. The aim of this study was to explore the anti-inflammatory action of polyphenols from I. sanghuang extract (ISE) in macrophages and the interaction between macrophages and adipocytes.Materials and Methods: RAW264.7 macrophages were stimulated with LPS or conditioned medium of hypertrophied 3T3-L1 adipocytes or cocultured with differentiated adipocytes in the presence of different doses of ISE. The inflammatory cytokines were evaluated by ELISA, the MAPK, NF-κB, and IL-6/STAT3 signals were determined by immunoblotting, and the migrated function of macrophages was determined by migration assay.Results: ISE suppressed the inflammatory mediators including NO, TNF-α, IL-6, and MCP-1 induced by either LPS or conditioned medium derived from 3T3-L1 adipocytes. ISE also decreased the production of these inflammatory mediators in cocultures of 3T3-L1 adipocytes and RAW264.7 macrophages. Furthermore, ISE blocked RAW264.7 macrophages migration toward 3T3-L1 adipocytes in cocultures. Finally, this effect of ISE might be mediated via inhibiting ERK, p38, and STAT3 activation.Conclusions: Our findings indicate the possibility that ISE suppresses the interaction between macrophages and adipocytes, attenuates chronic inflammation in adipose tissue and improves obesity-related insulin resistance and complication, suggesting that ISE might be a valuable medicinal food effective in improving insulin resistance and metabolic syndrome

Investigating the searching behavior of Sino-U.S. relations in China based on complex network

The Sino-U.S. relationship is one of the most important bilateral relationships in the literature of global geopolitics. Not only the two countries, but also other nations in the relevant regions have been influenced by their economic, cultural, political, educational, and diplomatic relations. In this paper, we have applied Visibility Graph as the method, analyzed the data from Baidu searching index of the keyword “Sino-U.S. relations” from 2011 to 2021 into a directionless and authoritarian network, and studied its dynamic characteristics. from the time series data, it has been found that the relationship between the data is closer with more edges, greater degrees, and greater clustering coefficients. Meanwhile, the shorter the average path length, the closer the relationship between the data. The results provide a new perspective for analyzing the time series characteristics of Sino-U.S. relations.</jats:p

Semi-Supervised Adversarial Transfer Networks for Cross-Domain Intelligent Fault Diagnosis of Rolling Bearings

In recent advances, deep learning-based methods have been broadly applied in fault diagnosis, while most existing studies assume that source domain and target domain data follow the same distribution. As differences in operating conditions lead to the deterioration of diagnosis performance, domain adaptation technology has been introduced to bridge the distribution gap. However, most existing approaches generally assume that source domain labels are available under all health conditions during training, which is incompatible with the actual industrial situation. To this end, this paper proposes a semi-supervised adversarial transfer networks for cross-domain intelligent fault diagnosis of rolling bearings. Firstly, the Gramian Angular Field method is introduced to convert time domain vibration signals into images. Secondly, a semi-supervised learning-based label generating module is designed to generate artificial labels for unlabeled images. Finally, the dynamic adversarial transfer network is proposed to extract the domain-invariant features of all signal images and provide reliable diagnosis results. Two case studies were conducted on public rolling bearing datasets to evaluate the diagnostic performance. An experiment under variable operating conditions and an experiment with different numbers of source domain labels were carried out to verify the generalization and robustness of the proposed approach, respectively. Experiment results demonstrate that the proposed method can achieve high diagnosis accuracy when dealing with cross-domain tasks with deficient source domain labels, which may be more feasible in engineering applications than conventional methodologies

Towards Sustainable Urbanization: Exploring the Influence Paths of the Urban Environment on Bidders’ Collusive Willingness

Collusive bidding is a severe unethical and illegal practice in urban construction projects. This practice has been identified as the primary inhibitor of sustainable urban development. Collusive bidding is formed and can be profoundly impacted by the urban environment. Identifying the transmission routes of the impacts of the urban environment on collusive bidding is conducive to urban governors formulating collusive governance countermeasures to create a healthy pace of urbanization. Therefore, this study adopts the bootstrap method to empirically analyze the influence paths from the urban environment to bidders’ collusive willingness. The data come from 675 collusion cases in China’s urban construction projects and city environmental data. The research concludes that the urban environment affects collusive willingness mainly through indirect pathways. The number of collusive companies is the most critical mediating variable in the indirect path. Besides, when the collusive project and leading colluder are in the same province, little indirect utility can also be transmitted through the project profitability. These findings extend the body of knowledge on collusion-related studies in urban research. The study also offers practical implications, suggesting that urban governors and owners should take countermeasures to increase the difficulty of bidders to form a collusion team, thereby inhibiting collusive bidding.</jats:p