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https://www.selleckchem.com/products/c-178.html Background Soil ecosystems consist of complex interactions between biological communities and physico-chemical variables, all of which contribute to the overall quality of soils. Despite this, changes in bacterial communities are ignored by most soil monitoring programs, which are crucial to ensure the sustainability of land management practices. We applied 16S rRNA gene sequencing to determine the bacterial community composition of over 3000 soil samples from 606 sites in New Zealand. Sites were classified as indigenous forests, exotic forest plantations, horticulture, or pastoral grasslands; soil physico-chemical variables related to soil quality were also collected. The composition of soil bacterial communities was then used to predict the land use and soil physico-chemical variables of each site. Results Soil bacterial community composition was strongly linked to land use, to the extent where it could correctly determine the type of land use with 85% accuracy. Despite the inherent variation introduced by uality. Video Abstract.An amendment to this paper has been published and can be accessed via the original article.Objectives The present database contains information on sociodemographic and clinical data as well as data from the Care Transition Measure (CTM 15-Brazil) of cancer patients undergoing clinical or surgical treatment. Data collection was carried out 7 to 30 days after patients' hospital discharge from June to August 2019. Understanding these data can contribute to improving quality of care transitions and avoiding hospital readmissions. Data description This data set encompasses 213 cancer patients characterized by the follow variables gender, age range, place of residence, race, marital status, schooling, paid work activity, type of treatment, cancer staging, metastasis, comorbidities, main complaint, main complaint grouped as, continuing medication, diagnosis, diagnosis grouped as, cancer type, year o

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