Citizen curation in online discussions of Donald Trump's presidency: sharing the news on Mumsnet.

In an era of fake news and concerns about social-media bubbles, we consider how participants in online discussions on the UK parenting website Mumsnet assess the validity and potential subjectivity of news information sources. Building on previous work on the phenomenon of social media curation and news curation, we argue that there is evidence for the development of a theory and practice of citizen curation - the subjective and non-professional collection, assessment and criticism of information by participants in online discussions for the benefit of the group. Participants on Mumsnet collaborate to source, present and curate information from a variety of news sources, and impose a clear hierarchy with reference to these sources' veracity. Information garnered from mainstream, liberal-leaning news sources is given the highest level of trust, often being used to support information from other sources, which are seen as less trust-worthy. Information might also be presented from conservative-leaning news sources, but only when it supports the overall anti-Trump tone. Having acknowledged the selective subjectivity of the curatorial process performed by our participants, we then ask how far this contributes to the creation of a liberal bubble effect, and how far our participants are willing to go to validate news stories shared in this way. We argue that our participants demonstrated a clear awareness of the veracity and potential subjectivity of their sources, worked collaboratively to verify news items, and were proud of their ability to scoop the mainstream news media on occasion. Given that earlier work on such groups of news-absorbed users has suggested that they tend to be male, the identification of such a group on a female-dominated website also expands the literature and suggests that such gender differentiations should be made with care

The Effects of Massage Therapy on Pain Management in the Acute Care Setting

Background: Pain management remains a critical issue for hospitals and is receiving the attention of hospital accreditation organizations. The acute care setting of the hospital provides an excellent opportunity for the integration of massage therapy for pain management into the team-centered approach of patient care. Purpose and Setting: This preliminary study evaluated the effect of the use of massage therapy on inpatient pain levels in the acute care setting. The study was conducted at Flagstaff Medical Center in Flagstaff, Arizona—a nonprofit community hospital serving a large rural area of northern Arizona. Method: A convenience sample was used to identify research participants. Pain levels before and after massage therapy were recorded using a 0 – 10 visual analog scale. Quantitative and qualitative methods were used for analysis of this descriptive study. Participants: Hospital inpatients (n = 53) from medical, surgical, and obstetrics units participated in the current research by each receiving one or more massage therapy sessions averaging 30 minutes each. The number of sessions received depended on the length of the hospital stay. Result: Before massage, the mean pain level recorded by the patients was 5.18 [standard deviation (SD): 2.01]. After massage, the mean pain level was 2.33 (SD: 2.10). The observed reduction in pain was statistically significant: paired samples t52 = 12.43, r = .67, d = 1.38, p < .001. Qualitative data illustrated improvement in all areas, with the most significant areas of impact reported being overall pain level, emotional well-being, relaxation, and ability to sleep. Conclusions: This study shows that integration of massage therapy into the acute care setting creates overall positive results in the patient’s ability to deal with the challenging physical and psychological aspects of their health condition. The study demonstrated not only significant reduction in pain levels, but also the interrelatedness of pain, relaxation, sleep, emotions, recovery, and finally, the healing process

Computerized clinical documentation system in the pediatric intensive care unit

BACKGROUND: To determine whether a computerized clinical documentation system (CDS): 1) decreased time spent charting and increased time spent in patient care; 2) decreased medication errors; 3) improved clinical decision making; 4) improved quality of documentation; and/or 5) improved shift to shift nursing continuity. METHODS: Before and after implementation of CDS, a time study involving nursing care, medication delivery, and normalization of serum calcium and potassium values was performed. In addition, an evaluation of completeness of documentation and a clinician survey of shift to shift reporting were also completed. This was a modified one group, pretest-posttest design. RESULTS: With the CDS there was: improved legibility and completeness of documentation, data with better accessibility and accuracy, no change in time spent in direct patient care or charting by nursing staff. Incidental observations from the study included improved management functions of our nurse manager; improved JCAHO documentation compliance; timely access to clinical data (labs, vitals, etc); a decrease in time and resource use for audits; improved reimbursement because of the ability to reconstruct lost charts; limited human data entry by automatic data logging; eliminated costs of printing forms. CDS cost was reasonable. CONCLUSIONS: When compared to a paper chart, the CDS provided a more legible, compete, and accessible patient record without affecting time spent in direct patient care. The availability of the CDS improved shift to shift reporting. Other observations showed that the CDS improved management capabilities; helped physicians deliver care; improved reimbursement; limited data entry errors; and reduced costs

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer’s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, ‘shape connections’ between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1–3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature

The impact of PICALM genetic variations on reserve capacity of posterior cingulate in AD continuum

Phosphatidylinositolbinding clathrin assembly protein (PICALM) gene is one novel genetic player associated with late-onset Alzheimer’s disease (LOAD), based on recent genome wide association studies (GWAS). However, how it affects AD occurrence is still unknown. Brain reserve hypothesis highlights the tolerant capacities of brain as a passive means to fight against neurodegenerations. Here, we took the baseline volume and/or thickness of LOAD-associated brain regions as proxies of brain reserve capacities and investigated whether PICALM genetic variations can influence the baseline reserve capacities and the longitudinal atrophy rate of these specific regions using data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. In mixed population, we found that brain region significantly affected by PICALM genetic variations was majorly restricted to posterior cingulate. In sub-population analysis, we found that one PICALM variation (C allele of rs642949) was associated with larger baseline thickness of posterior cingulate in health. We found seven variations in health and two variations (rs543293 and rs592297) in individuals with mild cognitive impairment were associated with slower atrophy rate of posterior cingulate. Our study provided preliminary evidences supporting that PICALM variations render protections by facilitating reserve capacities of posterior cingulate in non-demented elderly