Virtual patients design and its effect on clinical reasoning and student experience : a protocol for a randomised factorial multi-centre study

Background Virtual Patients (VPs) are web-based representations of realistic clinical cases. They are proposed as being an optimal method for teaching clinical reasoning skills. International standards exist which define precisely what constitutes a VP. There are multiple design possibilities for VPs, however there is little formal evidence to support individual design features. The purpose of this trial is to explore the effect of two different potentially important design features on clinical reasoning skills and the student experience. These are the branching case pathways (present or absent) and structured clinical reasoning feedback (present or absent). Methods/Design This is a multi-centre randomised 2x2 factorial design study evaluating two independent variables of VP design, branching (present or absent), and structured clinical reasoning feedback (present or absent).The study will be carried out in medical student volunteers in one year group from three university medical schools in the United Kingdom, Warwick, Keele and Birmingham. There are four core musculoskeletal topics. Each case can be designed in four different ways, equating to 16 VPs required for the research. Students will be randomised to four groups, completing the four VP topics in the same order, but with each group exposed to a different VP design sequentially. All students will be exposed to the four designs. Primary outcomes are performance for each case design in a standardized fifteen item clinical reasoning assessment, integrated into each VP, which is identical for each topic. Additionally a 15-item self-reported evaluation is completed for each VP, based on a widely used EViP tool. Student patterns of use of the VPs will be recorded. In one centre, formative clinical and examination performance will be recorded, along with a self reported pre and post-intervention reasoning score, the DTI. Our power calculations indicate a sample size of 112 is required for both primary outcomes

Introducing Comprehensive Community Needs Assessment

This article describes the Comprehensive Community Needs Assessment and how it seeks to contextualize ERW-related risks at community, mine-action-operator, national-authority and donor levels in order to prioritize community aid so funds are used effectively and communities receive the assistance they need

Rice Physical Defenses and Their Role Against Insect Herbivores

Plants have evolved a multi-layered defense system against the wide range of pests that constantly attack them. Physical defenses comprised of trichomes, wax, silica, callose, and lignin, and are considered as the first line of defense against herbivory that can directly affect herbivores by restricting or deterring them. Most studies on physical defenses against insect herbivores have been focused on dicots compared to monocots, although monocots include one of the most important crops, rice, which half of the global population is dependent on as their staple food. In rice, Silica is an important element stimulating plant growth, although Silica has also been found to impart resistance against herbivores. However, other physical defenses in rice including wax, trichomes, callose, and lignin are less explored. A detailed exploration of the morphological structures and functional consequences of physical defense structures in rice can assist in incorporating these resistance traits in plant breeding and genetic improvement programs, and thereby potentially reduce the use of chemicals in the field. This mini review addresses these points with a closer look at current literature and prospects on rice physical defenses

Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease

Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-β deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker

Clinical and Biomarker Changes in Dominantly Inherited Alzheimer's Disease

BACKGROUND: The order and magnitude of pathologic processes in Alzheimer's disease are not well understood, partly because the disease develops over many years. Autosomal dominant Alzheimer's disease has a predictable age at onset and provides an opportunity to determine the sequence and magnitude of pathologic changes that culminate in symptomatic disease. METHODS: In this prospective, longitudinal study, we analyzed data from 128 participants who underwent baseline clinical and cognitive assessments, brain imaging, and cerebrospinal fluid (CSF) and blood tests. We used the participant's age at baseline assessment and the parent's age at the onset of symptoms of Alzheimer's disease to calculate the estimated years from expected symptom onset (age of the participant minus parent's age at symptom onset). We conducted cross-sectional analyses of baseline data in relation to estimated years from expected symptom onset in order to determine the relative order and magnitude of pathophysiological changes. RESULTS: Concentrations of amyloid-beta (Aβ)(42) in the CSF appeared to decline 25 years before expected symptom onset. Aβ deposition, as measured by positron-emission tomography with the use of Pittsburgh compound B, was detected 15 years before expected symptom onset. Increased concentrations of tau protein in the CSF and an increase in brain atrophy were detected 15 years before expected symptom onset. Cerebral hypometabolism and impaired episodic memory were observed 10 years before expected symptom onset. Global cognitive impairment, as measured by the Mini-Mental State Examination and the Clinical Dementia Rating scale, was detected 5 years before expected symptom onset, and patients met diagnostic criteria for dementia at an average of 3 years after expected symptom onset. CONCLUSIONS: We found that autosomal dominant Alzheimer's disease was associated with a series of pathophysiological changes over decades in CSF biochemical markers of Alzheimer's disease, brain amyloid deposition, and brain metabolism as well as progressive cognitive impairment. Our results require confirmation with the use of longitudinal data and may not apply to patients with sporadic Alzheimer's disease. (Funded by the National Institute on Aging and others; DIAN ClinicalTrials.gov number, NCT00869817.)

Geriatric Assistive Device to Help In/Out of Bath

Final report for Team 18 of ME450, Fall 2008 semesterWith the "Baby Boomer" generation growing older and medicine advancing, the population of geriatric patients is rapidly rising. Getting into and out of the bath is a particularly difficult task. Working with Naomi Gilbert at the University Med. Rehab and Susan Murphy, an assistant professor for physical medicine and rehabilitation at the University of Michigan, our team will improve current assistive bath transfers on the market. Our team will design an assistive device that allows a geriatric patient independence while safely helping them get into and out of the bath.Naomi Gilbert (Med. Rehab, U of M) and Susan Murphy (Physical Medicine & Rehabilitation, U of M)http://deepblue.lib.umich.edu/bitstream/2027.42/61927/1/ME450 Fall2008 Final Report - Team 18 - Sliding Shower Chair.pd

ECOD: integrating classifications of protein domains from experimental and predicted structures.

The evolutionary classification of protein domains (ECOD) classifies protein domains using a combination of sequence and structural data (http://prodata.swmed.edu/ecod). Here we present the culmination of our previous efforts at classifying domains from predicted structures, principally from the AlphaFold Database (AFDB), by integrating these domains with our existing classification of PDB structures. This combined classification includes both domains from our previous, purely experimental, classification of domains as well as domains from our provisional classification of 48 proteomes in AFDB predicted from model organisms and organisms of concern to global health. ECOD classifies over 1.8 M domains from over 1000 000 proteins collectively deposited in the PDB and AFDB. Additionally, we have changed the F-group classification reference used for ECOD, deprecating our original ECODf library and instead relying on direct collaboration with the Pfam sequence family database to inform our classification. Pfam provides similar coverage of ECOD with family classification while being more accurate and less redundant. By eliminating duplication of effort, we can improve both classifications. Finally, we discuss the initial deployment of DrugDomain, a database of domain-ligand interactions, on ECOD and discuss future plans

The Effectiveness and Micro-costing Analysis of a Universal, School-Based, Social–Emotional Learning Programme in the UK: A Cluster-Randomised Controlled Trial

There are a growing number of school-based interventions designed to promote children’s social and emotional learning. One such intervention, PATHS (Promoting Alternative Thinking Strategies), was evaluated in a randomised controlled trial involving 5074 pupils aged 4–6 years at baseline in 56 primary schools across a large city in the UK. The programme was implemented for two academic years. The primary outcome measure was the teacher-rated Strengths and Difficulties Questionnaire (SDQ). A secondary measure was the PATHS Teacher Rating Scale (PTRS). Observations of child and teacher behaviours were undertaken in a third of intervention and control schools using the Teacher–Pupil Observation Tool (T-POT). Regarding fidelity, dose and adherence were measured via weekly logs completed by teachers, and a semi-structured questionnaire completed by PATHS coaches was used as a global measure of fidelity (capturing adherence, dose and quality). A cost-consequence analysis examined programme costs from a multi-agency public sector perspective. At 1 year post-baseline, there were no statistically significant differences between the programme and control groups on the SDQ subscales or the SDQ total difficulties and impact scores. There were statistically significant differences favouring the programme group for six out of 11 subscales on the secondary outcome measure (PTRS). At 2 years post-baseline, there were no statistically significant differences between the groups on either measure. Fidelity, according to the global measure, was relatively strong, and there was no relationship between fidelity and treatment effects. The average cost of PATHS was £12,666 per school or £139 per child. The study, which was fully powered and independent of the programme developer, shows no statistically significant effect of the programme on child behaviour or emotional well-being. Trial registration site and number: www.controlled-trials.com: ISRCTN 32534848

Autosomal-dominant Alzheimer's disease: a review and proposal for the prevention of Alzheimer's disease

Autosomal-dominant Alzheimer's disease has provided significant understanding of the pathophysiology of Alzheimer's disease. The present review summarizes clinical, pathological, imaging, biochemical, and molecular studies of autosomal-dominant Alzheimer's disease, highlighting the similarities and differences between the dominantly inherited form of Alzheimer's disease and the more common sporadic form of Alzheimer's disease. Current developments in autosomal-dominant Alzheimer's disease are presented, including the international Dominantly Inherited Alzheimer Network and this network's initiative for clinical trials. Clinical trials in autosomal-dominant Alzheimer's disease may test the amyloid hypothesis, determine the timing of treatment, and lead the way to Alzheimer's disease prevention

Data-driven models of dominantly-inherited Alzheimer’s disease progression

Dominantly-inherited Alzheimer's disease is widely hoped to hold the key to developing interventions for sporadic late onset Alzheimer's disease. We use emerging techniques in generative data-driven disease-progression modelling to characterise dominantly-inherited Alzheimer’s disease progression with unprecedented resolution, and without relying upon familial estimates of years until symptom onset (EYO). We retrospectively analysed biomarker data from the sixth data freeze of the Dominantly Inherited Alzheimer Network observational study, including measures of amyloid proteins and neurofibrillary tangles in the brain, regional brain volumes and cortical thicknesses, brain glucose hypometabolism, and cognitive performance from the Mini-Mental State Examination (all adjusted for age, years of education, sex, and head size, as appropriate). Data included 338 participants with known mutation status (211 mutation carriers: 163 PSEN1; 17 PSEN2; and 31 APP) and a baseline visit (age 19–66; up to four visits each, 1·1±1·9 years in duration; spanning 30 years before, to 21 years after, parental age of symptom onset). We used an event-based model to estimate sequences of biomarker changes from baseline data across disease subtypes (mutation groups), and a differential-equation model to estimate biomarker trajectories from longitudinal data (up to 66 mutation carriers, all subtypes combined). The two models concur that biomarker abnormality proceeds as follows: amyloid deposition in cortical then sub-cortical regions (approximately 24±11 years before onset); CSF p-tau (17±8 years), tau and Aβ42 changes; neurodegeneration first in the putamen and nucleus accumbens (up to 6±2 years); then cognitive decline (7±6 years), cerebral hypometabolism (4±4 years), and further regional neurodegeneration. Our models predicted symptom onset more accurately than EYO: root-mean-squared error of 1·35 years versus 5·54 years. The models reveal hidden detail on dominantly-inherited Alzheimer's disease progression, as well as providing data-driven systems for fine-grained patient staging and prediction of symptom onset with great potential utility in clinical trials