78 research outputs found
Living on the edge: utilising lidar data to assess the importance of vegetation structure for avian diversity in fragmented woodlands and their edges
Context: In agricultural landscapes, small woodland patches can be important wildlife refuges. Their value in maintaining biodiversity may, however, be compromised by isolation, and so knowledge about the role of habitat structure is vital to understand the drivers of diversity. This study examined how avian diversity and abundance were related to habitat structure in four small woods in an agricultural landscape in eastern England. Objectives: The aims were to examine the edge effect on bird diversity and abundance, and the contributory role of vegetation structure. Specifically: what is the role of vegetation structure on edge effects, and which edge structures support the greatest bird diversity? Methods: Annual breeding bird census data for 28 species were combined with airborne lidar data in linear mixed models fitted separately at (i) the whole wood level, and (ii) for the woodland edges only. Results: Despite relatively small woodland areas (4.9–9.4 ha), bird diversity increased significantly towards the edges, being driven in part by vegetation structure. At the whole woods level, diversity was positively associated with increased vegetation above 0.5 m and especially with increasing vegetation density in the understorey layer, which was more abundant at the woodland edges. Diversity along the edges was largely driven by the density of vegetation below 4 m. Conclusions: The results demonstrate that bird diversity was maximised by a diverse vegetation structure across the wood and especially a dense understorey along the edge. These findings can assist bird conservation by guiding habitat management of remaining woodland patches
Valor do EEG na caracterização e prognóstico de patologias neurológicas em recém-nascidos prematuros
Efficacy of a brief multifactorial adherence-based intervention on reducing the blood pressure of patients with poor adherence: protocol for a randomized clinical trial
<p>Abstract</p> <p>Background</p> <p>Lowering of blood pressure by antihypertensive drugs reduces the risks of cardiovascular events, stroke, and total mortality. However, poor adherence to antihypertensive medications reduces their effectiveness and increases the risk of adverse events. In terms of relative risk reduction, an improvement in medication adherence could be as effective as the development of a new drug.</p> <p>Methods/Design</p> <p>The proposed randomized controlled trial will include patients with a low adherence to medication and uncontrolled blood pressure. The intervention group will receive a multifactorial intervention during the first, third, and ninth months, to improve adherence. This intervention will include motivational interviews, pill reminders, family support, blood pressure self-recording, and simplification of the dosing regimen.</p> <p>Measurement</p> <p>The primary outcome is systolic blood pressure. The secondary outcomes are diastolic blood pressure, proportion of patients with adequately controlled blood pressure, and total cost.</p> <p>Discussion</p> <p>The trial will evaluate the impact of a multifactorial adherence intervention in routine clinical practice. Ethical approval was given by the Ethical Committee on Human Research of Balearic islands, Spain (approval number IB 969/08 PI).</p> <p>Trial registration</p> <p>Current controlled trials ISRCTN21229328</p
Probucol Release from Novel Multicompartmental Microcapsules for the Oral Targeted Delivery in Type 2 Diabetes
In previous studies, we developed and characterised multicompartmental microcapsules as a platform for the targeted oral delivery of lipophilic drugs in type 2 diabetes (T2D). We also designed a new microencapsulated formulation of probucol-sodium alginate (PB-SA), with good structural properties and excipient compatibility. The aim of this study was to examine the stability and pH-dependent targeted release of the microcapsules at various pH values and different temperatures. Microencapsulation was carried out using a Büchi-based microencapsulating system developed in our laboratory. Using SA polymer, two formulations were prepared: empty SA microcapsules (SA, control) and loaded SA microcapsules (PB-SA, test), at a constant ratio (1:30), respectively. Microcapsules were examined for drug content, zeta potential, size, morphology and swelling characteristics and PB release characteristics at pH 1.5, 3, 6 and 7.8. The production yield and microencapsulation efficiency were also determined. PB-SA microcapsules had 2.6 ± 0.25% PB content, and zeta potential of −66 ± 1.6%, suggesting good stability. They showed spherical and uniform morphology and significantly higher swelling at pH 7.8 at both 25 and 37°C (p < 0.05). The microcapsules showed multiphasic release properties at pH 7.8. The production yield and microencapsulation efficiency were high (85 ± 5 and 92 ± 2%, respectively). The PB-SA microcapsules exhibited distal gastrointestinal tract targeted delivery with a multiphasic release pattern and with good stability and uniformity. However, the release of PB from the microcapsules was not controlled, suggesting uneven distribution of the drug within the microcapsules
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
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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
Cognitive composites for genetic frontotemporal dementia: GENFI-Cog
Background
Clinical endpoints for upcoming therapeutic trials in frontotemporal dementia (FTD) are increasingly urgent. Cognitive composite scores are often used as endpoints but are lacking in genetic FTD. We aimed to create cognitive composite scores for genetic frontotemporal dementia (FTD) as well as recommendations for recruitment and duration in clinical trial design.
Methods
A standardized neuropsychological test battery covering six cognitive domains was completed by 69 C9orf72, 41 GRN, and 28 MAPT mutation carriers with CDR® plus NACC-FTLD ≥ 0.5 and 275 controls. Logistic regression was used to identify the combination of tests that distinguished best between each mutation carrier group and controls. The composite scores were calculated from the weighted averages of test scores in the models based on the regression coefficients. Sample size estimates were calculated for individual cognitive tests and composites in a theoretical trial aimed at preventing progression from a prodromal stage (CDR® plus NACC-FTLD 0.5) to a fully symptomatic stage (CDR® plus NACC-FTLD ≥ 1). Time-to-event analysis was performed to determine how quickly mutation carriers progressed from CDR® plus NACC-FTLD = 0.5 to ≥ 1 (and therefore how long a trial would need to be).
Results
The results from the logistic regression analyses resulted in different composite scores for each mutation carrier group (i.e. C9orf72, GRN, and MAPT). The estimated sample size to detect a treatment effect was lower for composite scores than for most individual tests. A Kaplan-Meier curve showed that after 3 years, ~ 50% of individuals had converted from CDR® plus NACC-FTLD 0.5 to ≥ 1, which means that the estimated effect size needs to be halved in sample size calculations as only half of the mutation carriers would be expected to progress from CDR® plus NACC FTLD 0.5 to ≥ 1 without treatment over that time period.
Discussion
We created gene-specific cognitive composite scores for C9orf72, GRN, and MAPT mutation carriers, which resulted in substantially lower estimated sample sizes to detect a treatment effect than the individual cognitive tests. The GENFI-Cog composites have potential as cognitive endpoints for upcoming clinical trials. The results from this study provide recommendations for estimating sample size and trial duration
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