A Systematic Visualization Review of Green Environment and Public Health for 2003-2019 Based on The Co-Citation Bibliometric Analysis Theory

Currently, the world is facing challenges of environmental pollution and public health owing to increasing urbanization. Therefore, many researchers from developed and developing countries are considering environmental pollution and public health to be the most important topics for sustainable development alongside a healthy and green environment. Although in the literature many researchers have investigated a pictorial view of green environment by defining the urban green space and blue space effects on public health, the green environments and public health research trend remains unclear. Thus, this study aimed to contribute to the literature by visualizing the bibliometric for green environments and public health, and to identify the missing research pathway. Data for this study was collected from the Web of Science from 2003-2019 in order to facilitate a visualization and bibliometric analysis carried out by CiteSpace. The visualization results reveal the most influential studies, institutions, authors, countries, keywords, and category cloud in the green environments and public health research field. Furthermore, this study suggests that researchers need to pay attention to how the genome changes due to climate change, as well as environmental pollution and its effect on human health. Mental health and research related to green environment and social health is also missing. In addition, there is also a missing link regarding green environment, underground water and public health. Additionally, this study could help authors and publishers make decisions concerning research on green environments and public health and planning for future perspectives to contribute to both academic development and applied methodology.

CyFi-MAP: an interactive pathway-based resource for cystic fibrosis

Cystic fibrosis (CF) is a life-threatening autosomal recessive disease caused by more than 2100 mutations in the CF transmembrane conductance regulator (CFTR) gene, generating variability in disease severity among individuals with CF sharing the same CFTR genotype. Systems biology can assist in the collection and visualization of CF data to extract additional biological significance and find novel therapeutic targets. Here, we present the CyFi-MAP—a disease map repository of CFTR molecular mechanisms and pathways involved in CF. Specifically, we represented the wild-type (wt-CFTR) and the F508del associated processes (F508del-CFTR) in separate submaps, with pathways related to protein biosynthesis, endoplasmic reticulum retention, export, activation/inactivation of channel function, and recycling/degradation after endocytosis. CyFi-MAP is an open-access resource with specific, curated and continuously updated information on CFTR-related pathways available online at https://cysticfibrosismap.github.io/. This tool was developed as a reference CF pathway data repository to be continuously updated and used worldwide in CF research.

The Traditional Chinese Medicine Compound Huangqin Qingre Chubi Capsule Inhibits the Pathogenesis of Rheumatoid Arthritis Through the CUL4B/Wnt Pathway

The pathogenesis of rheumatoid arthritis (RA) is still not fully clarified, and the development of therapeutic drugs for RA is particularly urgent. Our group studies a possibility that circ_ 0015756/miR-942-5p may participate in the pathogenesis of RA through disordered Cullin 4B (CUL4B) and the traditional Chinese medicine compound Huangqin Qingre Chubi Capsule (HQC) may inhibit the pathogenesis of RA through the CUL4B/Wnt pathway. Data showed that the expression of circ_0015756 increased not only in fibroblast-like synoviocytes (FLS) of RA, but also in synovium and FLS of CIA mice, and the expression of miR-942-5p decreased. Abnormal circ_0015756 up-regulated the CUL4B expression and activated the canonical Wnt signaling pathway by inhibiting the expression of miR-942-5p. Circ_0015756 participated in the pathogenesis of RA and promoted the abnormal proliferation of FLS. Further, circ_0015756 activated the secretion of IL-1 and IL-8 and promoted the production of RA pathological gene MMP3 and fibronectin. Further analysis showed that HQC inhibited the pathogenesis of RA through the CUL4B/Wnt pathway, and the specific target was CUL4B. HQC interfered with the effects of circ_0015756 on the pathogenesis of RA by inhibiting the CUL4B, showing a good therapeutic effect on RA.

Value configurations for balancing standardization and customization in chronic care: a qualitative study

Background Demands for both customization and standardization are increasing in healthcare. At the same time, resources are scarce, and healthcare managers are urged to improve efficiency. A framework of three value configurations – shop, chain, and network – has been proposed for how healthcare operations can be designed and organized for efficient value creation. In this paper, use of value configurations for balancing of standardization and customization is explored in the context of care for chronic mental conditions. Methods A typical case is presented to illustrate the manifestations of conflicting demands between customization and standardization, and the potential usefulness of the value configurations framework. Qualitative data were collected from managers and care developers in two focus groups and six semi-structured interviews, completed by a national document describing a care pathway. Data were coded and analysed using an insider-outsider approach. Results Operationalization of the balance between standardization and customization were found to be highly delegated and ad hoc. Also, the conflict between the two demands was often seen as aggravated by scarce resources. Value configurations can be fruitful as a means of discussing and redesigning care operations if applied at a suitable level of abstraction. Applied adequately, all three value configurations were recognized in the care operations for the patient group, with shop as the overarching configuration. Some opportunities for improved efficiency were identified, yet all configurations were seen as vital in the chronic care process. Conclusions The study challenges the earlier proposed organizational separation of care corresponding to different value configurations. Instead, as dual demand for customization and standardization permeates healthcare, parallel but explicated value configurations may be a path to improved quality and efficiency. Combined and intermediate configurations should also be further investigated.

Dissecting immune cell stat regulation network reveals biomarkers to predict ICB therapy responders in melanoma

Background Immunotherapy is a revolutionary strategy in cancer therapy, but the resistance of which is one of the important challenges. Detecting the regulation of immune cells and biomarkers concerning immune checkpoint blockade (ICB) therapy is of great significance. Methods Here, we firstly constructed regulation networks for 11 immune cell clusters by integrating biological pathway data and single cell sequencing data in metastatic melanoma with or without ICB therapy. We then dissected these regulation networks and identified differently expressed genes between responders and non-responders. Finally, we trained and validated a logistic regression model based on ligands and receptors in the regulation network to predict ICB therapy response. Results We discovered the regulation of genes across eleven immune cell stats. Functional analysis indicated that these stat-specific networks consensually enriched in immune response corrected pathways and highlighted antigen processing and presentation as a core pathway in immune cell regulation. Furthermore, some famous ligands like SIRPA, ITGAM, CD247and receptors like CD14, IL2 and HLA-G were differently expressed between cells of responders and non-responders. A predictive model of gene sets containing ligands and receptors performed accuracy prediction with AUCs above 0.7 in a validation dataset suggesting that they may be server as biomarkers for predicting immunotherapy response. Conclusions In summary, our study presented the gene–gene regulation landscape across 11 immune cell clusters and analysis of these networks revealed several important aspects and immunotherapy response biomarkers, which may provide novel insights into immune related mechanisms and immunotherapy response prediction.

DecoPath: a web application for decoding pathway enrichment analysis

The past decades have brought a steady growth of pathway databases and enrichment methods. However, the advent of pathway data has not been accompanied by an improvement in interoperability across databases, hampering the use of pathway knowledge from multiple databases for enrichment analysis. While integrative databases have attempted to address this issue, they often do not account for redundant information across resources. Furthermore, the majority of studies that employ pathway enrichment analysis still rely upon a single database or enrichment method, though the use of another could yield differing results. These shortcomings call for approaches that investigate the differences and agreements across databases and methods as their selection in the design of a pathway analysis can be a crucial step in ensuring the results of such an analysis are meaningful. Here we present DecoPath, a web application to assist in the interpretation of the results of pathway enrichment analysis. DecoPath provides an ecosystem to run enrichment analysis or directly upload results and facilitate the interpretation of results with custom visualizations that highlight the consensus and/or discrepancies at the pathway- and gene-levels. DecoPath is available at https://decopath.scai.fraunhofer.de, and its source code and documentation can be found on GitHub at https://github.com/DecoPath/DecoPath.

DecoPath: A web application for decoding pathway enrichment analysis

The past two decades have brought a steady growth of pathway databases and pathway enrichment methods. However, the advent of pathway data has not been accompanied by an improvement with regards to interoperability across databases, thus, hampering the use of pathway knowledge from multiple databases for pathway enrichment analyses. While integrative databases have attempted to address this issue by collating pathway knowledge from multiple resources, these approaches do not account for redundant information across them. On the other hand, the majority of studies that employ pathway enrichment analyses still rely upon a single database, though the use of another resource could yield differing results, which is similarly the case when different pathway enrichment methods are employed. These shortcomings call for approaches that investigate the differences and agreements across databases and enrichment methods as their selection in the experimental design of a pathway analysis can be a crucial first step in ensuring the results of such an analysis are meaningful. Here we present DecoPath, a web application to assist in the interpretation of the results of pathway enrichment analysis. DecoPath provides an ecosystem to run pathway enrichment analysis or directly upload results and facilitate the interpretation of these results with custom visualizations that highlight the consensus and/or discrepancies at the pathway- and gene-levels. DecoPath is available at https://decopath.scai.fraunhofer.de and its source code and documentation can be found on GitHub at https://github.com/DecoPath/DecoPath.

415 Improving Preoperative Computed Tomography Staging for Men with Suspected Testicular Cancer

Introduction Neo-adjuvant chemotherapy may be considered for suspected testicular malignancy if widespread life-threatening metastases are identified on computed tomography (CT) imaging. Staging preoperatively enables this and may prevent delays in ongoing oncological care. This project aimed to increase the proportion of staging scans performed preoperatively in the University Hospitals of Leicester NHS trust. Method All referrals between 01/01/2016 and 31/12/2018 to the urology multidisciplinary team for suspected testicular cancer were reviewed. Exclusion criteria were applied prior to collecting treatment pathway data for each patient. Based on initial audit findings, clinicians were advised to request staging CT scans at the first urology clinic appointment. Re-audit was between 01/01/2019 and 31/12/2019. Results Initial audit included 95 patients and re-audit included 23 patients. The proportion of preoperative scans increased from 28.4% to 82.6% following intervention. Median time from first ultrasound to CT was reduced from 44 days to 17 days without affecting median time to orchidectomy (27 to 23 days) or oncology appointment (61 days). Conclusions Requesting a staging CT scan as part of the first clinic assessment improved the proportion of preoperative scans without affecting time to surgery or oncology appointment.

749 Delivering Safe and Timely Cancer Care During COVID 19. Lessons and Successes from The Transition Period

Introduction Delivering timely cancer care during the COVID-19 pandemic was a major challenge. We analysed our success in addressing this. Method A key factor was the proximity of a private hospital (GN) to the primary trust. GN acted as a ‘clean site’. From 6th April 2020, two robots and dedicated staff were relocated to day surgery theatres with direct access to GN. Procedures and post-operative recovery happened in GN. National surgical guidelines were followed related to Covid-19. All theatre staff were swabbed weekly. Patients were risk stratified prior to admittance. Results We reviewed operations performed and cancer pathway data from March to June 2020 and compared it to data collected from August to November 2019. From March until June 2020 we performed 369 cancer operations; 120 robotic, 138 endoscopic and 7 open cases. From August to November 2019 we performed 407 cancer operations; 116 robotic, 175 endoscopic and 7 open cases. No elective patient developed symptomatic COVID-19 secondary to admission. Conclusions This study demonstrates that with rapid development of separate ‘clean’ and ‘COVID’ sites, we successfully delivered a comparable, safe and effective cancer service. As we potentially face a second wave we share our success to see if these changes can be replicated elsewhere.

PaIRKAT: A pathway integrated regression-based kernel association test with applications to metabolomics and COPD phenotypes

High-throughput data such as metabolomics, genomics, transcriptomics, and proteomics have become familiar data types within the "-omics" family. For this work, we focus on subsets that interact with one another and represent these "pathways" as graphs. Observed pathways often have disjoint components, i.e. nodes or sets of nodes (metabolites, etc.) not connected to any other within the pathway which notably lessens testing power. In this paper we propose the Pathway Integrated Regression-based Kernel Association Test (PaIRKAT), a new kernel machine regression method for incorporating known pathway information into the semi-parametric kernel regression framework. This paper also contributes an application of a graph kernel regularization method for overcoming disconnected pathways. By incorporating a regularized or "smoothed" graph into a score test, PaIRKAT is capable of providing more powerful tests for associations between biological pathways and phenotypes of interest and will be helpful in identifying novel pathways for targeted clinical research. We evaluate this method through several simulation studies and an application to real metabolomics data from the COPDGene study. Our simulation studies illustrate the robustness of this method to incorrect and incomplete pathway knowledge, and the real data analysis shows meaningful improvements of testing power in pathways. PaIRKAT was developed for application to metabolomic pathway data, but the techniques are easily generalizable to other data sources with a graph-like structure.