ABSTRACT
Hemp (Cannabis sativa L.) has historically played a vital role in agriculture across the globe. Feral and wild populations have served as genetic resources for breeding, conservation, and adaptation to changing environmental conditions. However, feral populations of Cannabis, specifically in the Midwestern United States, remain poorly understood. This study aims to characterize the abiotic tolerances of these populations, estimate suitable areas, identify regions at risk of abiotic suitability change, and highlight the utility of ecological niche models (ENMs) in germplasm conservation. The Maxent algorithm was used to construct a series of ENMs. Validation metrics and MOP (Mobility-oriented Parity) analysis were used to assess extrapolation risk and model performance. We also projected the final projected under current and future climate scenarios (2021-2040 and 2061-2080) to assess how abiotic suitability changes with time. Climate change scenarios indicated an expansion of suitable habitat, with priority areas for germplasm collection in Indiana, Illinois, Kansas, Missouri, and Nebraska. This study demonstrates the application of ENMs for characterizing feral Cannabis populations and highlights their value in germplasm conservation and breeding efforts. Populations of feral C. sativa in the Midwest are of high interest, and future research should focus on utilizing tools to aid the collection of materials for the characterization of genetic diversity and adaptation to a changing climate.
ABSTRACT
OBJECTIVES: The aim of this systematic review was to summarize national and international guidelines that made recommendations for monitoring patients diagnosed with low-risk cancer. It appraised the quality of guidelines and determined whether the guidelines adequately identified patients for monitoring, specified which tests to use, defined monitoring intervals, and stated triggers for further intervention. It then assessed the evidence to support each recommendation. STUDY DESIGN AND SETTING: Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses, we searched PubMed and Turning Research into Practice databases for national and international guidelines' that were written in English and developed or updated between 2012 and 2023. Quality of individual guidelines was assessed using the AGREE II tool. RESULTS: Across the 41 published guidelines, 48 different recommendations were identified: 15 (31%) for prostate cancer, 11 (23%) for renal cancer, 6 (12.5%) for thyroid cancer, and 10 (21%) for blood cancer. The remaining 6 (12.5%) were for brain, gastrointestinal, oral cavity, bone and pheochromocytoma and paraganglioma cancer. When combining all guidelines, 48 (100%) stated which patients qualify for monitoring, 31 (65%) specified which tests to use, 25 (52%) provided recommendations for surveillance intervals, and 23 (48%) outlined triggers to initiate intervention. Across all cancer sites, there was a strong positive trend with higher levels of evidence being associated with an increased likelihood of a recommendation being specific (P = 0.001) and the evidence for intervals was based on expert opinion or other guidance. CONCLUSION: With the exception of prostate cancer, the evidence base for monitoring low-risk cancer is weak and consequently recommendations in clinical guidelines are inconsistent. There is a lack of direct evidence to support monitoring recommendations in the literature making guideline developers reliant on expert opinion, alternative guidelines, or indirect or nonspecific evidence.
Subject(s)
Neoplasms , Practice Guidelines as Topic , Humans , Practice Guidelines as Topic/standards , Neoplasms/therapy , Male , FemaleABSTRACT
INTRODUCTION: Treatment-resistant depression (TRD) is depression unresponsive to antidepressants and affects 55% of British primary care users with depression. Current evidence is from secondary care, but long referral times mean general practitioners (GPs) manage TRD. Studies show that people with depression use Twitter to form community and document symptoms. However, Twitter remains a largely unexplored space of documented patient experience. Twitter data could provide valuable insights into learning about primary care experiences of TRD. In this study, we explored Twitter comments and conversations about TRD and produced patient-driven recommendations. METHODS: Tweets from UK-based users were collected manually and using a browser extension in June 2021. Conventional content analysis was used to provide an overview of the Tweets, followed by interpretation to understand why Twitter may be important to people with TRD. RESULTS: A total of 415 Tweets were organised into five clusters: self-diagnosis, symptoms, support, small wins and condition experts. These Tweets were interpreted as showing Twitter as a community for people with TRD. People had a collective sense of illness identity and were united in their experiences of TRD. However, users in the community also highlighted the absence of effective GP care, leading users to position themselves as condition experts. Users shared advice from a place of lived experience with the community but also shared potentially harmful information, including recommendations about nonevidence-based medications. CONCLUSIONS: Findings illuminate the benefits of the TRD Twitter community and also highlight that the perception of a lack of knowledge and support from GPs may lead community members to advise nonevidenced-based medications. PATIENT AND PUBLIC CONTRIBUTION: This study was led by a person with lived experience of TRD and bipolar. Two public contributors with mental health conditions gave feedback on our study protocol and results.
