Notes

Recognition and also Functional Characterization associated with 2 Homologous SpoVS Protein Involved with Sporulation of Bacillus thuringiensis.
OBJECTIVE This study aimed to explore whether positive impacts were sustained and unanticipated ripple effects had occurred four years after the implementation of interventions to improve cross-cultural communication in primary care. BACKGROUND Sustaining the implementation of change using complex interventions is challenging. The EU-funded "RESTORE" study implemented guidelines and training on cross-cultural communication in five Primary Care sites in Europe, combining implementation theory (Normalisation Process Theory) with participatory methodology (participatory learning and action-PLA). There were positive impacts on knowledge, skills and clinical routines. DESIGN, SETTING AND PARTICIPANTS Four of the five original sites (England, Ireland, Greece, The Netherlands) were available for this qualitative follow-up study. The study population (N = 44) was primary healthcare staff and migrants, most of whom had participated in RESTORE. INTERVENTION; MAIN OUTCOME MEASURES PLA-style focus groups and interviews explored routine practice during consultations with migrants. Etic cards based on the effects of RESTORE stimulated the discussion. Deductive framework analysis was performed in each country followed by comparative data analysis and synthesis. RESULTS Changes in knowledge, attitudes and behaviour with regard to consultations with migrants were sustained and migrants felt empowered by their participation in RESTORE. There were ongoing concerns about macro level factors, like the political climate and financial policies, negatively affecting migrant healthcare. CONCLUSION There were sustained effects in clinical settings, and additional unanticipated positive ripple effects, due in part, from the participatory approach employed. © 2020 The Authors Health Expectations published by John Wiley & Sons Ltd.Groundwater temperature is a useful hydrogeological parameter that is easy to measure and can provide much insight into groundwater flow systems, but can be difficult to interpret. For measuring temperature directly in the ground, dedicated specifically designed monitoring wells are recommended since conventional groundwater wells are not optimal for temperature monitoring. Multilevel monitoring of groundwater temperature is required to identify contributions of different possible heat inputs (sources) on measured temperature signals. Interpreting temperature data as a cosine function, including period, average temperature, amplitude, and phase offset, is helpful. Amplitude dampening and increasing phase shift with distance from a boundary can be used for estimation of transport parameters. Temperature measurements at different depths can be used for evaluation of unknown parameters of analytical functions by optimization of regression fits in Python. These estimated parameters can be used to calculate temperatures at known water table depths which can be applied as a fixed transient boundary condition in MT3DMS to overcome the limitations of MT3DMS heat transport modeling in the unsaturated zone. In this study, temperature monitoring and modeling was used to evaluate the influence of a department store's heated basement foundation on groundwater temperature within a green space (city park), with the main outcome that 17 years after construction, the department store foundation has increased the mean groundwater temperature by 3.2 °C. Heat input evaluated by the MT3DMS model varied from 0.1 W/m2 at a distance of 100 m up to 12 W/m2 next to the building. © 2020, National Ground Water Association.BACKGROUND With the development of research on cancer genomics and microenvironment, a new era of oncology focusing on the complicated gene regulation of pan-cancer research and cancer immunotherapy is emerging. This study aimed to identify the common gene expression characteristics of multiple cancers - lung cancer, liver cancer, kidney cancer, cervical cancer, and breast cancer - and the potential therapeutic targets in public databases. GCN2iB mw MATERIAL AND METHODS Gene expression analysis of GSE42568, GSE19188, GSE121248, GSE63514, and GSE66272 in the GEO database of multitype cancers revealed differentially expressed genes (DEGs). Then, GO analysis, KEGG function, and path enrichment analyses were performed. Hub-genes were identified by using the degree of association of protein interaction networks. Moreover, the expression of hub-genes in cancers was verified, and hub-gene-related survival analysis was conducted. Finally, infiltration levels of tumor immune cells with related genes were explored. RESULTS We found 12 cross DEGs in the 5 databases (screening conditions "adj p2 or logFC less then -2"). The biological processes of DEGs were mainly concentrated in cell division, regulation of chromosome segregation, nuclear division, cell cycle checkpoint, and mitotic nuclear division. Furthermore, 10 hub-genes were obtained using Cytoscape TOP2A, ECT2, RRM2, ANLN, NEK2, ASPM, BUB1B, CDK1, DTL, and PRC1. The high expression levels of the 10 genes were associated with the poor survival of these multiple cancers, as well as ASPM, may be associated with immune cell infiltration. CONCLUSIONS Analysis of the common DEGs of multiple cancers showed that 10 hub-genes, especially ASPM and CDK1, can become potential therapeutic targets. This study can serve as a reference to understand the characteristics of different cancers, design basket clinical trials, and create personalized treatments.No Abstract Available.No Abstract Available.No Abstract Available.No Abstract Available.BACKGROUND Pre-clinical studies suggest that metformin and statins may delay prostate cancer (PCa) metastases; however, data in humans are limited. To the best of our knowledge, this is the first human study aimed to quantify the individual and joint effects of statin and metformin use among patients with high-risk PCa. METHODS This population-based retrospective cohort study identified patients from the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database. Exposure to metformin and statins was ascertained from Medicare Prescription Drug Event files. The association with all-cause and PCa mortality were evaluated using Cox proportional hazard model with competing causes of death, where propensity scores were used to adjusted imbalances in covariates across groups. RESULTS Based on 12 700 patients with high-risk PCa, statin alone or in combination with metformin was significantly associated with reduced all-cause mortality (Hazard Ratio [HR] 0.89; 95% Confidence Interval [CI] 0.83, 0.96; and HR 0.
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