The implementation of a Technician Enhanced Administration of Medications [TEAM] model: An evaluative study of impact on working practices in a children's hospital

Background: Children are frequently prescribed unlicensed and off-label medicines meaning dosing and administration of medicines to children is often based on poor quality guidance. In UK hospitals, nursing staff are often responsible for administering medications. Medication Errors [MEs] are problematic for health services, though are poorly reported and therefore difficult to quantify with confidence. In the UK, children's medicines require administration by at least two members of ward staff, known as a ‘second check’ system, thought to reduce Medication Administration Errors [MAEs]. Objectives: To assess the impact on working practices of the introduction of a new way of working, using Technician Enhanced Administration of Medications [TEAM] on two specialist wards within a children's’ hospital. To evidence any potential impact of a TEAM ward-based pharmacy technician [PhT] on the reporting of MEs. Methods: A TEAM PhT was employed on two wards within the children's hospital and trained in medicines administration. Firstly, an observational pre-and-post cohort design was used to identify the effect of TEAM on MEs. We analysed the hospital's official reporting system for incidents and ‘near misses’, as well as the personal incident log of the TEAM PhT. Secondly, after implementation, we interviewed staff about their perceptions of TEAM and its impact on working practices. Results: We affirm MEs are considerably under-reported in hospital settings, but TEAM PhTs can readily identify them. Further, placing TEAM PhTs on wards may create opportunities for inter-professional knowledge exchange and increase nurses’ awareness of potential MAEs, although this requires facilitation. Conclusions: TEAM PhT roles may be beneficial for pharmacy technicians’ motivation, job satisfaction, and career development. Hospitals will need to consider the balance between resources invested in TEAM PhTs and the level of impact on reporting MEs. Health economic analyses could provide evidence to fully endorse integration of TEAM PhTs for all hospital settings

Novel epigenetic clock for fetal brain development predicts prenatal age for cellular stem cell models and derived neurons

Induced pluripotent stem cells (iPSCs) and their differentiated neurons (iPSC-neurons) are a widely used cellular model in the research of the central nervous system. However, it is unknown how well they capture age-associated processes, particularly given that pluripotent cells are only present during the earliest stages of mammalian development. Epigenetic clocks utilize coordinated age-associated changes in DNA methylation to make predictions that correlate strongly with chronological age. It has been shown that the induction of pluripotency rejuvenates predicted epigenetic age. As existing clocks are not optimized for the study of brain development, we developed the fetal brain clock (FBC), a bespoke epigenetic clock trained in human prenatal brain samples in order to investigate more precisely the epigenetic age of iPSCs and iPSC-neurons. The FBC was tested in two independent validation cohorts across a total of 194 samples, confirming that the FBC outperforms other established epigenetic clocks in fetal brain cohorts. We applied the FBC to DNA methylation data from iPSCs and embryonic stem cells and their derived neuronal precursor cells and neurons, finding that these cell types are epigenetically characterized as having an early fetal age. Furthermore, while differentiation from iPSCs to neurons significantly increases epigenetic age, iPSC-neurons are still predicted as being fetal. Together our findings reiterate the need to better understand the limitations of existing epigenetic clocks for answering biological research questions and highlight a limitation of iPSC-neurons as a cellular model of age-related diseases

Promoter Methylation in Head and Neck Squamous Cell Carcinoma Cell Lines Is Significantly Different than Methylation in Primary Tumors and Xenografts

Studies designed to identify novel methylation events related to cancer often employ cancer cell lines in the discovery phase of the experiments and have a relatively low rate of discovery of cancer-related methylation events. An alternative algorithm for discovery of novel methylation in cancer uses primary tumor-derived xenografts instead of cell lines as the primary source of nucleic acid for evaluation. We evaluated DNA extracted from primary head and neck squamous cell carcinomas (HNSCC), xenografts grown from these primary tumors in nude mice, HNSCC-derived cell lines, normal oral mucosal samples, and minimally transformed oral keratinocyte-derived cell lines using Illumina Infinum Humanmethylation 27 genome-wide methylation microarrays. We found >2,200 statistically significant methylation differences between cancer cell lines and primary tumors and when comparing normal oral mucosa to keratinocyte cell lines. We found no statistically significant promoter methylation differences between primary tumor xenografts and primary tumors. This study demonstrates that tumor-derived xenografts are highly accurate representations of promoter methylation in primary tumors and that cancer derived cell lines have significant drawbacks for discovery of promoter methylation alterations in primary tumors. These findings also support use of primary tumor xenografts for the study of methylation in cancer, drug discovery, and the development of personalized cancer treatments

Digital Cranial Endocast of Hyopsodus (Mammalia, “Condylarthra”): A Case of Paleogene Terrestrial Echolocation?

We here describe the endocranial cast of the Eocene archaic ungulate Hyopsodus lepidus AMNH 143783 (Bridgerian, North America) reconstructed from X-ray computed microtomography data. This represents the first complete cranial endocast known for Hyopsodontinae. The Hyopsodus endocast is compared to other known “condylarthran” endocasts, i. e. those of Pleuraspidotherium (Pleuraspidotheriidae), Arctocyon (Arctocyonidae), Meniscotherium (Meniscotheriidae), Phenacodus (Phenacodontidae), as well as to basal perissodactyls (Hyracotherium) and artiodactyls (Cebochoerus, Homacodon). Hyopsodus presents one of the highest encephalization quotients of archaic ungulates and shows an “advanced version” of the basal ungulate brain pattern, with a mosaic of archaic characters such as large olfactory bulbs, weak ventral expansion of the neopallium, and absence of neopallium fissuration, as well as more specialized ones such as the relative reduction of the cerebellum compared to cerebrum or the enlargement of the inferior colliculus. As in other archaic ungulates, Hyopsodus midbrain exposure is important, but it exhibits a dorsally protruding largely developed inferior colliculus, a feature unique among “Condylarthra”. A potential correlation between the development of the inferior colliculus in Hyopsodus and the use of terrestrial echolocation as observed in extant tenrecs and shrews is discussed. The detailed analysis of the overall morphology of the postcranial skeleton of Hyopsodus indicates a nimble, fast moving animal that likely lived in burrows. This would be compatible with terrestrial echolocation used by the animal to investigate subterranean habitat and/or to minimize predation during nocturnal exploration of the environment

Pairing of Homologous Regions in the Mouse Genome Is Associated with Transcription but Not Imprinting Status

This work was funded by the BBSRC, grant BB/H088071/1 (www.bbsrc.ac.uk), MRC, grant G0700760 (www.mrc.ac.uk), Wellcome Trust, grant 095645/Z/11/Z (www.wellcome.ac.uk) and the EU through EpiGeneSys (www.epigenesys.eu) and Blueprint (www.blueprint-epigenome.eu). C.K. was funded by the DFG, personal fellowship KR 3317/2-1 (www.dfg.de) and CTR, personal short term fellowship (www.trophoblast.cam.ac.uk). M.J.H. received funding through grant NCI/NIH 2RO1 CA089426 (www.nih.gov)

Chronic widespread musculoskeletal pain, fatigue, depression and disordered sleep in chronic post-SARS syndrome; a case-controlled study

<p>Abstract</p> <p>Background</p> <p>The long term adverse effects of Severe Acute Respiratory Syndrome (SARS), a viral disease, are poorly understood.</p> <p>Methods</p> <p>Sleep physiology, somatic and mood symptoms of 22 Toronto subjects, 21 of whom were healthcare workers, (19 females, 3 males, mean age 46.29 yrs.+/- 11.02) who remained unable to return to their former occupation (mean 19.8 months, range: 13 to 36 months following SARS) were compared to 7 healthy female subjects. Because of their clinical similarities to patients with fibromyalgia syndrome (FMS) these post-SARS subjects were similarly compared to 21 drug free female patients, (mean age 42.4 +/- 11.8 yrs.) who fulfilled criteria for fibromyalgia.</p> <p>Results</p> <p>Chronic post-SARS is characterized by persistent fatigue, diffuse myalgia, weakness, depression, and nonrestorative sleep with associated REM-related apneas/hypopneas, an elevated sleep EEG cyclical alternating pattern, and alpha EEG sleep anomaly. Post- SARS patients had symptoms of pre and post-sleep fatigue and post sleep sleepiness that were similar to the symptoms of patients with FMS, and similar to symptoms of patients with chronic fatigue syndrome. Both post-SARS and FMS groups had sleep instability as indicated by the high sleep EEG cyclical alternating pattern rate. The post-SARS group had a lower rating of the alpha EEG sleep anomaly as compared to the FMS patients. The post-SARS group also reported less pre-sleep and post-sleep musculoskeletal pain symptoms.</p> <p>Conclusions</p> <p>The clinical and sleep features of chronic post-SARS form a syndrome of chronic fatigue, pain, weakness, depression and sleep disturbance, which overlaps with the clinical and sleep features of FMS and chronic fatigue syndrome.</p

Use of communities of practice in business and health care sectors: A systematic review

<p>Abstract</p> <p>Background</p> <p>Since being identified as a concept for understanding knowledge sharing, management, and creation, communities of practice (CoPs) have become increasingly popular within the health sector. The CoP concept has been used in the business sector for over 20 years, but the use of CoPs in the health sector has been limited in comparison.</p> <p>Objectives</p> <p>First, we examined how CoPs were defined and used in these two sectors. Second, we evaluated the evidence of effectiveness on the health sector CoPs for improving the uptake of best practices and mentoring new practitioners.</p> <p>Methods</p> <p>We conducted a search of electronic databases in the business, health, and education sectors, and a hand search of key journals for primary studies on CoP groups. Our research synthesis for the first objective focused on three areas: the authors' interpretations of the CoP concept, the key characteristics of CoP groups, and the common elements of CoP groups. To examine the evidence on the effectiveness of CoPs in the health sector, we identified articles that evaluated CoPs for improving health professional performance, health care organizational performance, professional mentoring, and/or patient outcome; and used experimental, quasi-experimental, or observational designs.</p> <p>Results</p> <p>The structure of CoP groups varied greatly, ranging from voluntary informal networks to work-supported formal education sessions, and from apprentice training to multidisciplinary, multi-site project teams. Four characteristics were identified from CoP groups: social interaction among members, knowledge sharing, knowledge creation, and identity building; however, these were not consistently present in all CoPs. There was also a lack of clarity in the responsibilities of CoP facilitators and how power dynamics should be handled within a CoP group. We did not find any paper in the health sector that met the eligibility criteria for the quantitative analysis, and so the effectiveness of CoP in this sector remained unclear.</p> <p>Conclusion</p> <p>There is no dominant trend in how the CoP concept is operationalized in the business and health sectors; hence, it is challenging to define the parameters of CoP groups. This may be one of the reasons for the lack of studies on the effectiveness of CoPs in the health sector. In order to improve the usefulness of the CoP concept in the development of groups and teams, further research will be needed to clarify the extent to which the four characteristics of CoPs are present in the mature and emergent groups, the expectations of facilitators and other participants, and the power relationship within CoPs.</p

Comparison of clinical rating scales in genetic frontotemporal dementia within the GENFI cohort

BACKGROUND: Therapeutic trials are now underway in genetic forms of frontotemporal dementia (FTD) but clinical outcome measures are limited. The two most commonly used measures, the Clinical Dementia Rating (CDR)+National Alzheimer’s Disease Coordinating Center (NACC) Frontotemporal Lobar Degeneration (FTLD) and the FTD Rating Scale (FRS), have yet to be compared in detail in the genetic forms of FTD. METHODS: The CDR+NACC FTLD and FRS were assessed cross-sectionally in 725 consecutively recruited participants from the Genetic FTD Initiative: 457 mutation carriers (77 microtubule-associated protein tau (MAPT), 187 GRN, 193 C9orf72) and 268 family members without mutations (non-carrier control group). 231 mutation carriers (51 MAPT, 92 GRN, 88 C9orf72) and 145 non-carriers had available longitudinal data at a follow-up time point. RESULTS: Cross-sectionally, the mean FRS score was lower in all genetic groups compared with controls: GRN mutation carriers mean 83.4 (SD 27.0), MAPT mutation carriers 78.2 (28.8), C9orf72 mutation carriers 71.0 (34.0), controls 96.2 (7.7), p<0.001 for all comparisons, while the mean CDR+NACC FTLD Sum of Boxes was significantly higher in all genetic groups: GRN mutation carriers mean 2.6 (5.2), MAPT mutation carriers 3.2 (5.6), C9orf72 mutation carriers 4.2 (6.2), controls 0.2 (0.6), p<0.001 for all comparisons. Mean FRS score decreased and CDR+NACC FTLD Sum of Boxes increased with increasing disease severity within each individual genetic group. FRS and CDR+NACC FTLD Sum of Boxes scores were strongly negatively correlated across all mutation carriers (r_{s} =−0.77, p<0.001) and within each genetic group (r_{s} =−0.67 to −0.81, p<0.001 in each group). Nonetheless, discrepancies in disease staging were seen between the scales, and with each scale and clinician-judged symptomatic status. Longitudinally, annualised change in both FRS and CDR+NACC FTLD Sum of Boxes scores initially increased with disease severity level before decreasing in those with the most severe disease: controls −0.1 (6.0) for FRS, −0.1 (0.4) for CDR+NACC FTLD Sum of Boxes, asymptomatic mutation carriers −0.5 (8.2), 0.2 (0.9), prodromal disease −2.3 (9.9), 0.6 (2.7), mild disease −10.2 (18.6), 3.0 (4.1), moderate disease −9.6 (16.6), 4.4 (4.0), severe disease −2.7 (8.3), 1.7 (3.3). Sample sizes were calculated for a trial of prodromal mutation carriers: over 180 participants per arm would be needed to detect a moderate sized effect (30%) for both outcome measures, with sample sizes lower for the FRS. CONCLUSIONS: Both the FRS and CDR+NACC FTLD measure disease severity in genetic FTD mutation carriers throughout the timeline of their disease, although the FRS may be preferable as an outcome measure. However, neither address a number of key symptoms in the FTD spectrum, for example, motor and neuropsychiatric deficits, which future scales will need to incorporate

A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia

Supplementary material: Supplementary material is available at Brain online: https://oup.silverchair-cdn.com/oup/backfile/Content_public/Journal/brain/145/5/10.1093_brain_awab382/1/awab382_supplementary_data.zip?Expires=1665139578&Signature=C7VStQxldRqnpcchAWh4igaKwveciF~gaQCbInqMnI1YkIFV0euPXlI-0ZlRZ26hbRum6myjm88d3KzOM-wqVG~H7JO9TTUXoyi-n3hRRd1a4Vw0Hay9ykagca92gMqWij5ax4WzsEGlv~dKGSKKivH02pflzQyDAwF6xjjObYRYe29grdOZQ5h8orT6XNAdK5YFqpiX7L6mpVaNs7AOgNDdxtwshaa4kq1xxCgojTgAaIR3WFTFDpHkJ6wnhncxuteykTzq5~w1RCoDIfKQSA9C42i~iWryOeOvjv-P6j-R0tSkDGzFKcI3kUo3lUT9GiPG-vDwAO5EsLkUikJLOw__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA.GENFI consortium members Full details are available in the Supplementary material. Sónia Afonso, Maria Rosario Almeida, Sarah Anderl-Straub, Christin Andersson, Anna Antonell, Silvana Archetti, Andrea Arighi, Mircea Balasa, Myriam Barandiaran, Nuria Bargalló, Robart Bartha, Benjamin Bender, Alberto Benussi, Luisa Benussi, Valentina Bessi, Giuliano Binetti, Sandra Black, Martina Bocchetta, Sergi Borrego-Ecija, Jose Bras, Rose Bruffaerts, Marta Cañada, Valentina Cantoni, Paola Caroppo, David Cash, Miguel Castelo-Branco, Rhian Convery, Thomas Cope, Giuseppe Di Fede, Alina Díez, Diana Duro, Chiara Fenoglio, Camilla Ferrari, Catarina B. Ferreira, Nick Fox, Morris Freedman, Giorgio Fumagalli, Alazne Gabilondo, Roberto Gasparotti, Serge Gauthier, Stefano Gazzina, Giorgio Giaccone, Ana Gorostidi, Caroline Greaves, Rita Guerreiro, Tobias Hoegen, Begoña Indakoetxea, Vesna Jelic, Hans-Otto Karnath, Ron Keren, Tobias Langheinrich, Maria João Leitão, Albert Lladó, Gemma Lombardi, Sandra Loosli, Carolina Maruta, Simon Mead, Gabriel Miltenberger, Rick van Minkelen, Sara Mitchell, Katrina Moore, Benedetta Nacmias, Jennifer Nicholas, Linn Öijerstedt, Jaume Olives, Sebastien Ourselin, Alessandro Padovani, Georgia Peakman, Michela Pievani, Yolande Pijnenburg, Cristina Polito, Enrico Premi, Sara Prioni, Catharina Prix, Rosa Rademakers, Veronica Redaelli, Tim Rittman, Ekaterina Rogaeva, Pedro Rosa-Neto, Giacomina Rossi, Martin Rosser, Beatriz Santiago, Elio Scarpini, Sonja Schönecker, Elisa Semler, Rachelle Shafei, Christen Shoesmith, Miguel Tábuas-Pereira, Mikel Tainta, Ricardo Taipa, David Tang-Wai, David L Thomas, Paul Thompson, Hakan Thonberg, Carolyn Timberlake, Pietro Tiraboschi, Emily Todd, Philip Van Damme, Mathieu Vandenbulcke, Michele Veldsman, Ana Verdelho, Jorge Villanua, Jason Warren, Ione Woollacott, Elisabeth Wlasich, Miren Zulaica.Copyright © The Author(s) 2021. Several CSF and blood biomarkers for genetic frontotemporal dementia have been proposed, including those reflecting neuroaxonal loss (neurofilament light chain and phosphorylated neurofilament heavy chain), synapse dysfunction [neuronal pentraxin 2 (NPTX2)], astrogliosis (glial fibrillary acidic protein) and complement activation (C1q, C3b). Determining the sequence in which biomarkers become abnormal over the course of disease could facilitate disease staging and help identify mutation carriers with prodromal or early-stage frontotemporal dementia, which is especially important as pharmaceutical trials emerge. We aimed to model the sequence of biomarker abnormalities in presymptomatic and symptomatic genetic frontotemporal dementia using cross-sectional data from the Genetic Frontotemporal dementia Initiative (GENFI), a longitudinal cohort study. Two-hundred and seventy-five presymptomatic and 127 symptomatic carriers of mutations in GRN, C9orf72 or MAPT, as well as 247 non-carriers, were selected from the GENFI cohort based on availability of one or more of the aforementioned biomarkers. Nine presymptomatic carriers developed symptoms within 18 months of sample collection ('converters'). Sequences of biomarker abnormalities were modelled for the entire group using discriminative event-based modelling (DEBM) and for each genetic subgroup using co-initialized DEBM. These models estimate probabilistic biomarker abnormalities in a data-driven way and do not rely on previous diagnostic information or biomarker cut-off points. Using cross-validation, subjects were subsequently assigned a disease stage based on their position along the disease progression timeline. CSF NPTX2 was the first biomarker to become abnormal, followed by blood and CSF neurofilament light chain, blood phosphorylated neurofilament heavy chain, blood glial fibrillary acidic protein and finally CSF C3b and C1q. Biomarker orderings did not differ significantly between genetic subgroups, but more uncertainty was noted in the C9orf72 and MAPT groups than for GRN. Estimated disease stages could distinguish symptomatic from presymptomatic carriers and non-carriers with areas under the curve of 0.84 (95% confidence interval 0.80-0.89) and 0.90 (0.86-0.94) respectively. The areas under the curve to distinguish converters from non-converting presymptomatic carriers was 0.85 (0.75-0.95). Our data-driven model of genetic frontotemporal dementia revealed that NPTX2 and neurofilament light chain are the earliest to change among the selected biomarkers. Further research should investigate their utility as candidate selection tools for pharmaceutical trials. The model's ability to accurately estimate individual disease stages could improve patient stratification and track the efficacy of therapeutic interventions.Deltaplan Dementie (The Netherlands Organisation for Health Research and Development and Alzheimer Nederland; grant numbers 733050813,733050103 and 733050513), the Bluefield Project to Cure Frontotemporal Dementia, the Dioraphte founda tion (grant number 1402 1300), the European Joint Programme— Neurodegenerative Disease Research and the Netherlands Organisation for Health Research and Development (PreFrontALS: 733051042, RiMod-FTD: 733051024); V.V. and S.K. have received funding from the European Union’s Horizon 2020 research and in novation programme under grant agreement no. 666992 (EuroPOND). E.B. was supported by the Hartstichting (PPP Allowance, 2018B011); in Belgium by the Mady Browaeys Fonds voor Onderzoek naar Frontotemporale Degeneratie; in the UK by the MRC UK GENFI grant (MR/M023664/1); J.D.R. is supported by an MRC Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH); I.J.S. is supported by the Alzheimer’s Association; J.B.R. is supported by the Wellcome Trust (103838); in Spain by the Fundacio´ Marato´ de TV3 (20143810 to R.S.V.); in Germany by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy—ID 390857198) and by grant 779357 ‘Solve-RD’ from the Horizon 2020 Research and Innovation Programme (to MS); in Sweden by grants from the Swedish FTD Initiative funded by the Scho¨rling Foundation, grants from JPND PreFrontALS Swedish Research Council (VR) 529–2014-7504, Swedish Research Council (VR) 2015–02926, Swedish Research Council (VR) 2018–02754, Swedish Brain Foundation, Swedish Alzheimer Foundation, Stockholm County Council ALF, Swedish Demensfonden, Stohnes foundation, Gamla Tja¨narinnor, Karolinska Institutet Doctoral Funding and StratNeuro. H.Z. is a Wallenberg Scholar