Investigated individual and cultural correlates of survey response styles using a multilevel analysis approach to cultural models of self-construal. Data collected by V. L. Vignoles et al. (in press) ...for 7,122 survey respondents from 55 different cultures across 33 nations were reanalyzed. 35 self-construal items reflecting both Likert-type response scales and S. H. Schwartz's (2007) portrait-comparison response scales were used. Using Vignoles' seven dimensions of self-other relatedness, the results revealed both individual- and culture-level variations across response formats. Likert-scale response formats elicited the greatest acquiescence among individuals who view themselves as similar to others, and who live in cultures that emphasize social harmony and social receptiveness. In contrast, portrait-comparison response formats elicited the greatest acquiescence in individuals who viewed themselves as self-reliant but socially connected, and who live in cultures that espouse self-reliance and self-consistency. Extreme responding varied less across response formats, and was most common among individuals who view themselves as self-reliant. Implications for the valid cross-cultural comparison of empirical data are discussed. (ZPID).
Collation of aphasia research data across settings, countries and study designs using big data principles will support analyses across different language modalities, levels of impairment, and therapy ...interventions in this heterogeneous population. Big data approaches in aphasia research may support vital analyses, which are unachievable within individual trial datasets. However, we lack insight into the requirements for a systematically created database, the feasibility and challenges and potential utility of the type of data collated.
To report the development, preparation and establishment of an internationally agreed aphasia after stroke research database of individual participant data (IPD) to facilitate planned aphasia research analyses.
Data were collated by systematically identifying existing, eligible studies in any language (≥10 IPD, data on time since stroke, and language performance) and included sourcing from relevant aphasia research networks. We invited electronic contributions and also extracted IPD from the public domain. Data were assessed for completeness, validity of value-ranges within variables, and described according to pre-defined categories of demographic data, therapy descriptions, and language domain measurements. We cleaned, clarified, imputed and standardised relevant data in collaboration with the original study investigators. We presented participant, language, stroke, and therapy data characteristics of the final database using summary statistics.
From 5256 screened records, 698 datasets were potentially eligible for inclusion; 174 datasets (5928 IPD) from 28 countries were included, 47/174 RCT datasets (1778 IPD) and 91/174 (2834 IPD) included a speech and language therapy (SLT) intervention. Participants' median age was 63 years (interquartile range 53, 72), 3407 (61.4%) were male and median recruitment time was 321 days (IQR 30, 1156) after stroke. IPD were available for aphasia severity or ability overall (n = 2699; 80 datasets), naming (n = 2886; 75 datasets), auditory comprehension (n = 2750; 71 datasets), functional communication (n = 1591; 29 datasets), reading (n = 770; 12 datasets) and writing (n = 724; 13 datasets). Information on SLT interventions were described by theoretical approach, therapy target, mode of delivery, setting and provider. Therapy regimen was described according to intensity (1882 IPD; 60 datasets), frequency (2057 IPD; 66 datasets), duration (1960 IPD; 64 datasets) and dosage (1978 IPD; 62 datasets).
Our international IPD archive demonstrates the application of big data principles in the context of aphasia research; our rigorous methodology for data acquisition and cleaning can serve as a template for the establishment of similar databases in other research areas.
We are developing an imaging capability (“Hyperspectral X-ray Imaging”) for mapping chemical information (molecular formula, phase, oxidation state, hydration) that is based on ultra-high-resolution ...X-ray emission spectroscopy with large transition-edge sensor microcalorimeter arrays in the scanning electron microscope. By combining microcalorimeter arrays with hundreds of pixels, high-bandwidth microwave frequency-division multiplexing, and fast digital electronics for near real-time data processing, our goal is to enable measurements using laboratory-scale instrumentation rather than synchrotron beamlines. Our application focus here is on mapping the chemical form of uranium compounds on the nanoscale. We will present our approach to developing the Hyperspectral X-ray Imaging capability, progress toward a 128-pixel microwave multiplexed X-ray fluorescence instrument at LANL, and the path to high-throughput nanoscale chemical mapping.
Abstract
Background
Hippocampal atrophy is observed in Alzheimer’s disease (AD), but also in older adults with no evidence of amyloid‐β (Aβ) plaques. To understand the pathophysiology of hippocampal ...volume (HV) loss, we investigated the associations between longitudinal HV, age, genotype, Aβ, and tau in clinically normal (CN) participants from the Harvard Aging Brain Study.
Method
Serial MRI (HV 1.3‐7.0y, PiB‐PET (Aβ, 1.9‐8.5y), and Flortaucipir‐PET (tau, 0.8‐6.0y) measures were obtained from 128CN participants (72 56% females, 38 30% e4 carriers, median age at baseline: 71.3, follow‐up duration: 5.1y). Participants had a median of 3MRIs 2‐5, 3PiB‐PET 2‐5, and 2Flortaucipir‐PET 2‐4. Longitudinal HVs were processed using Freesurfer v.6 and adjusted for intracranial volume. PiB was measured in a neocortical aggregate, Flortaucipir in inferior temporal (IT) and entorhinal cortex (EC). PET data were expressed as PVC‐SUVr scaled to subcortical white matter. We predicted imaging data over time with random intercept and slope in linear mixed‐models and extracted PiB, FTP, and HV slopes for each subject. Baseline PET and slope data were entered in age‐adjusted linear regressions to evaluate their associations with HV slope.
Result
Faster HV loss was observed at older ages (Figure 1), and marginally in e4 carriers (Table, #1‐2). It was also associated with higher baseline PiB levels (#3). The PiB association was stronger than the one of e4 status (#3). HV slope did not correlate with PiB slope (#4). HV loss was associated with baseline EC‐FTP (#5) and baseline IT‐FTP (#6). The association between HV loss and EC‐FTP was also observed in the low‐PiB only (#7), but not the one with IT‐FTP (#8). IT‐FTP, but not EC‐FTP, interacted with baseline PiB to predict HV slope (Figure 2‐3). FTP slopes measures were associated with HV slope, above and beyond the baseline association (#9‐10). Altogether PET data explained 40% of the variance in HV slope; but faster HV loss was still associated with age after taking PET measures into account.
Conclusion
In preclinical AD, hippocampal atrophy is associated with an Aβ‐independent entorhinal tau accumulation and an Aβ‐dependent neocortical tau accumulation. It is also likely associated with pathological processes that our biomarkers did not measure.
Background
Hippocampal atrophy is observed in Alzheimer’s disease (AD), but also in older adults with no evidence of amyloid‐β (Aβ) plaques. To understand the pathophysiology of hippocampal volume ...(HV) loss, we investigated the associations between longitudinal HV, age, genotype, Aβ, and tau in clinically normal (CN) participants from the Harvard Aging Brain Study.
Method
Serial MRI (HV 1.3‐7.0y, PiB‐PET (Aβ, 1.9‐8.5y), and Flortaucipir‐PET (tau, 0.8‐6.0y) measures were obtained from 128CN participants (72 56% females, 38 30% e4 carriers, median age at baseline: 71.3, follow‐up duration: 5.1y). Participants had a median of 3MRIs 2‐5, 3PiB‐PET 2‐5, and 2Flortaucipir‐PET 2‐4. Longitudinal HVs were processed using Freesurfer v.6 and adjusted for intracranial volume. PiB was measured in a neocortical aggregate, Flortaucipir in inferior temporal (IT) and entorhinal cortex (EC). PET data were expressed as PVC‐SUVr scaled to subcortical white matter. We predicted imaging data over time with random intercept and slope in linear mixed‐models and extracted PiB, FTP, and HV slopes for each subject. Baseline PET and slope data were entered in age‐adjusted linear regressions to evaluate their associations with HV slope.
Result
Faster HV loss was observed at older ages (Figure 1), and marginally in e4 carriers (Table, #1‐2). It was also associated with higher baseline PiB levels (#3). The PiB association was stronger than the one of e4 status (#3). HV slope did not correlate with PiB slope (#4). HV loss was associated with baseline EC‐FTP (#5) and baseline IT‐FTP (#6). The association between HV loss and EC‐FTP was also observed in the low‐PiB only (#7), but not the one with IT‐FTP (#8). IT‐FTP, but not EC‐FTP, interacted with baseline PiB to predict HV slope (Figure 2‐3). FTP slopes measures were associated with HV slope, above and beyond the baseline association (#9‐10). Altogether PET data explained 40% of the variance in HV slope; but faster HV loss was still associated with age after taking PET measures into account.
Conclusion
In preclinical AD, hippocampal atrophy is associated with an Aβ‐independent entorhinal tau accumulation and an Aβ‐dependent neocortical tau accumulation. It is also likely associated with pathological processes that our biomarkers did not measure.
Quantification of land surface–atmosphere fluxes of carbon dioxide
(CO2) and their trends and uncertainties is essential for
monitoring progress of the EU27+UK bloc as it strives to meet ambitious
...targets determined by both international agreements and internal regulation.
This study provides a consolidated synthesis of fossil sources (CO2
fossil) and natural (including formally managed ecosystems) sources and
sinks over land (CO2 land) using bottom-up (BU) and top-down (TD)
approaches for the European Union and United Kingdom (EU27+UK), updating
earlier syntheses (Petrescu et al., 2020, 2021). Given the wide scope of
the work and the variety of approaches involved, this study aims to answer
essential questions identified in the previous syntheses and understand the
differences between datasets, particularly for poorly characterized fluxes
from managed and unmanaged ecosystems. The work integrates updated emission
inventory data, process-based model results, data-driven categorical model
results, and inverse modeling estimates, extending the previous period
1990–2018 to the year 2020 to the extent possible. BU and TD products are
compared with the European national greenhouse gas inventory (NGHGI)
reported by parties including the year 2019 under the United Nations
Framework Convention on Climate Change (UNFCCC). The uncertainties of the
EU27+UK NGHGI were evaluated using the standard deviation reported by the
EU member states following the guidelines of the Intergovernmental Panel on
Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in
estimates produced with other methods, such as atmospheric inversion models
(TD) or spatially disaggregated inventory datasets (BU), originate from
within-model uncertainty related to parameterization as well as structural
differences between models. By comparing the NGHGI with other approaches,
key sources of differences between estimates arise primarily in activities.
System boundaries and emission categories create differences in CO2
fossil datasets, while different land use definitions for reporting
emissions from land use, land use change, and forestry (LULUCF) activities
result in differences for CO2 land. The latter has important
consequences for atmospheric inversions, leading to inversions reporting
stronger sinks in vegetation and soils than are reported by the NGHGI. For CO2 fossil emissions, after harmonizing
estimates based on common activities and selecting the most recent year
available for all datasets, the UNFCCC NGHGI for the EU27+UK accounts for
926 ± 13 Tg C yr−1, while eight other BU sources report a mean
value of 948 937,961 Tg C yr−1 (25th, 75th percentiles). The
sole top-down inversion of fossil emissions currently available accounts for
875 Tg C in this same year, a value outside the uncertainty of both the
NGHGI and bottom-up ensemble estimates and for which uncertainty estimates
are not currently available. For the net CO2 land fluxes, during the most recent 5-year period including the NGHGI
estimates, the NGHGI accounted for −91 ± 32 Tg C yr−1, while six
other BU approaches reported a mean sink of −62 -117,-49 Tg C yr−1,
and a 15-member ensemble of dynamic global vegetation models (DGVMs)
reported −69 -152,-5 Tg C yr−1. The 5-year mean of three TD
regional ensembles combined with one non-ensemble inversion of −73 Tg C yr−1 has a slightly smaller spread (0th–100th percentiles of
-135,+45 Tg C yr−1), and it was calculated after removing net
land–atmosphere CO2 fluxes caused by lateral transport of carbon (crop
trade, wood trade, river transport, and net uptake from inland water bodies),
resulting in increased agreement with the NGHGI and bottom-up approaches.
Results at the category level (Forest Land, Cropland, Grassland) generally show good agreement between the NGHGI and category-specific models, but
results for DGVMs are mixed. Overall, for both CO2 fossil and net
CO2 land fluxes, we find that current independent approaches are consistent
with the NGHGI at the scale of the EU27+UK. We conclude that CO2
emissions from fossil sources have decreased over the past 30 years in the
EU27+UK, while land fluxes are relatively stable: positive or negative
trends larger (smaller) than 0.07 (−0.61) Tg C yr−2 can be ruled out
for the NGHGI. In addition, a gap on the order of 1000 Tg C yr−1
between CO2 fossil emissions and net CO2 uptake by the land exists
regardless of the type of approach (NGHGI, TD, BU), falling well outside all
available estimates of uncertainties. However, uncertainties in top-down
approaches to estimate CO2 fossil emissions remain uncharacterized and
are likely substantial, in addition to known uncertainties in top-down
estimates of the land fluxes. The data used to plot the figures are
available at https://doi.org/10.5281/zenodo.8148461 (McGrath et al., 2023).
Quantification of land surface-atmosphere fluxes of carbon dioxide (CO.sub.2) and their trends and uncertainties is essential for monitoring progress of the EU27+UK bloc as it strives to meet ...ambitious targets determined by both international agreements and internal regulation. This study provides a consolidated synthesis of fossil sources (CO.sub.2 fossil) and natural (including formally managed ecosystems) sources and sinks over land (CO.sub.2 land) using bottom-up (BU) and top-down (TD) approaches for the European Union and United Kingdom (EU27+UK), updating earlier syntheses (Petrescu et al., 2020, 2021). Given the wide scope of the work and the variety of approaches involved, this study aims to answer essential questions identified in the previous syntheses and understand the differences between datasets, particularly for poorly characterized fluxes from managed and unmanaged ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven categorical model results, and inverse modeling estimates, extending the previous period 1990-2018 to the year 2020 to the extent possible. BU and TD products are compared with the European national greenhouse gas inventory (NGHGI) reported by parties including the year 2019 under the United Nations Framework Convention on Climate Change (UNFCCC). The uncertainties of the EU27+UK NGHGI were evaluated using the standard deviation reported by the EU member states following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), originate from within-model uncertainty related to parameterization as well as structural differences between models. By comparing the NGHGI with other approaches, key sources of differences between estimates arise primarily in activities. System boundaries and emission categories create differences in CO.sub.2 fossil datasets, while different land use definitions for reporting emissions from land use, land use change, and forestry (LULUCF) activities result in differences for CO.sub.2 land. The latter has important consequences for atmospheric inversions, leading to inversions reporting stronger sinks in vegetation and soils than are reported by the NGHGI.
Background: Speech and language therapy (SLT) benefits people with aphasia following stroke. Group level summary statistics from randomised controlled trials hinder exploration of highly complex SLT ...interventions and a clinically relevant heterogeneous population. Creating a database of individual participant data (IPD) for people with aphasia aims to allow exploration of individual and therapy-related predictors of recovery and prognosis.
Aim: To explore the contribution that individual participant characteristics (including stroke and aphasia profiles) and SLT intervention components make to language recovery following stroke.
Methods and procedures: We will identify eligible IPD datasets (including randomised controlled trials, non-randomised comparison studies, observational studies and registries) and invite their contribution to the database. Where possible, we will use meta- and network meta-analysis to explore language performance after stroke and predictors of recovery as it relates to participants who had no SLT, historical SLT or SLT in the primary research study. We will also examine the components of effective SLT interventions.
Outcomes and results: Outcomes include changes in measures of functional communication, overall severity of language impairment, auditory comprehension, spoken language (including naming), reading and writing from baseline. Data captured on assessment tools will be collated and transformed to a standardised measure for each of the outcome domains.
Conclusion: Our planned systematic-review-based IPD meta- and network meta-analysis is a large scale, international, multidisciplinary and methodologically complex endeavour. It will enable hypotheses to be generated and tested to optimise and inform development of interventions for people with aphasia after stroke.
Systematic review registration: The protocol has been registered at the International Prospective Register of Systematic Reviews (PROSPERO; registration number: CRD42018110947)
Accidental Pig Vaccine Injection Injury Van Demark, Robert E.; Hofer, Kevin L.; Tjarks, B. Joel ...
Journal of hand surgery global online,
10/2019, Letnik:
1, Številka:
4
Journal Article
Recenzirano
Odprti dostop
Animal vaccine injection injuries of the hand are of special concern in veterinary medicine and agricultural fields. Although most of these injuries resolve with no or minimal treatment, major ...complications can occur. We report a case of a farmworker who experienced an accidental needlestick injury while vaccinating pigs. The operative findings, postoperative course, and treatment options for vaccine needlestick injuries are discussed. Key words: accidental injection, animal vaccine injuries, high-pressure injection injuries, needlestick injuries, vaccine injuries
PDF
