The plant hormone cytokinin regulates many aspects of growth and development. Cytokinin signaling involves His kinase receptors that perceive cytokinin and transmit the signal via a multistep ...phosphorelay similar to bacterial two-component signaling systems. The final targets of this phosphorelay are a set of Arabidopsis thaliana Response Regulator (ARR) proteins containing a receiver domain with a conserved Asp phosphorylation site. One class of these, the type-A ARRs, are negative regulators of cytokinin signaling that are rapidly transcriptionally upregulated in response to cytokinin. In this study, we tested the role of phosphorylation in type-A ARR function. Our results indicate that phosphorylation of the receiver domain is required for type-A ARR function and suggest that negative regulation of cytokinin signaling by the type-A ARRs most likely involves phosphorylation-dependent interactions. Furthermore, we show that a subset of the type-A ARR proteins are stabilized in response to cytokinin in part via phosphorylation. These studies shed light on the mechanism by which type-A ARRs act to negatively regulate cytokinin signaling and reveal a novel mechanism by which cytokinin controls type-A ARR function.
MRI assessment of the brain has demonstrated four different patterns of atrophy in patients with Alzheimer's disease dementia (AD): typical AD, limbic-predominant AD, hippocampal-sparing AD, and a ...subtype with minimal atrophy, previously referred to as no-atrophy AD. The aim of the present study was to identify and describe the differences between these four AD subtypes in a longitudinal memory-clinic study.
The medial temporal lobes, the frontal regions, and the posterior regions were assessed with MRI visual rating scales to categorize 123 patients with mild AD according to ICD-10 and NINCDS-ADRDA criteria and the clinical dementia rating scale (CDR) into atrophy subtypes. Demographic data, neuropsychological measures, cerebrospinal-fluid biomarkers, and progression rate of dementia at two-year follow-up were compared between the groups.
Typical AD was found in 59 patients (48%); 29 (24%) patients had limbic-predominant AD; 19 (15%) had hippocampal-sparing AD; and 16 (13%) belonged to the group with minimal atrophy. No differences were found regarding cognitive test results or progression rates between the different subtypes. Using adjusted logistic regression analysis, we found that the patients in the minimal-atrophy group were less educated, had a lower baseline CDR sum of boxes score, and had higher levels of amyloid β in the cerebrospinal fluid.
Previous results concerning the prevalence and the similar phenotypic expressions of the four AD subtypes were confirmed. The main finding was that patients with minimal atrophy as assessed by MRI had less education than the other AD subtypes and that this could support the cognitive reserve hypothesis and, at least in part, explain the lower degree of atrophy in this group. Patients with less formal education might present with clinically typical AD symptoms before they have positive biomarkers of AD and this finding might challenge suggested biomarker-based criteria for AD.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
•The performance of a deep learning model for visual ratings of atrophy was investigated in clinical out-of-distribution data.•Model is more robust on unseen clinical data when trained on more ...heterogeneous training data.•Model trained on research data with harmonized protocols perform well in cohorts where data is acquired with similar scanning parameters but fails in others.
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Deep learning (DL) methods have in recent years yielded impressive results in medical imaging, with the potential to function as clinical aid to radiologists. However, DL models in medical imaging are often trained on public research cohorts with images acquired with a single scanner or with strict protocol harmonization, which is not representative of a clinical setting. The aim of this study was to investigate how well a DL model performs in unseen clinical datasets–collected with different scanners, protocols and disease populations–and whether more heterogeneous training data improves generalization. In total, 3117 MRI scans of brains from multiple dementia research cohorts and memory clinics, that had been visually rated by a neuroradiologist according to Scheltens’ scale of medial temporal atrophy (MTA), were included in this study. By training multiple versions of a convolutional neural network on different subsets of this data to predict MTA ratings, we assessed the impact of including images from a wider distribution during training had on performance in external memory clinic data. Our results showed that our model generalized well to datasets acquired with similar protocols as the training data, but substantially worse in clinical cohorts with visibly different tissue contrasts in the images. This implies that future DL studies investigating performance in out-of-distribution (OOD) MRI data need to assess multiple external cohorts for reliable results. Further, by including data from a wider range of scanners and protocols the performance improved in OOD data, which suggests that more heterogeneous training data makes the model generalize better. To conclude, this is the most comprehensive study to date investigating the domain shift in deep learning on MRI data, and we advocate rigorous evaluation of DL models on clinical data prior to being certified for deployment.
To compare in vitro failure loads of nerve coaptations using fibrin glue alone, a suture alone, and a combination of fibrin glue and a suture.
The median, radial, and ulnar nerves of 15 fresh-frozen ...cadaveric upper extremity specimens (45 nerves in total) were dissected in vitro and transected 5 cm proximal to the wrist crease to simulate an injury requiring coaptation. Three coaptation techniques were used: fibrin glue alone, a suture alone, and a suture augmented with fibrin glue. The load to failure of each repair was measured using a linear servo-actuator with an in-line force sensor. The results were analyzed using 2-way repeated measures analysis of variance tests and pairwise comparisons with Bonferroni correction.
Both the nerve coaptation technique and the specific nerve that was repaired had a significant effect on failure load. Suture-glue repair had the highest load to failure, 11.2 ± 2.9 N, and significantly increased the load to failure by 2.9 ± 1.7 N compared with glue repair alone. There was no significant difference between suture-glue repair and suture repair alone or between glue repair alone and suture repair alone.
In this in vitro cadaveric model, nerve injury coaptation using both a suture and fibrin glue resulted in the strongest repair. The addition of fibrin glue may provide some benefit when used to augment suture repair, but when used in isolation, it is inferior to combined suture-and-glue constructs.
Combined suture-and-glue nerve coaptations might be useful in the early postoperative period in increasing nerve repair strength and potentially reducing rupture rates.
Abstract only
Background:
Direct oral anticoagulants (DOACs) have progressively replaced vitamin K antagonists (VKAs). However, in certain conditions, especially antiphospholipid syndrome, mechanical ...heart valves and rheumatic mitral stenosis, VKAs remain the only drugs with established safety and efficacy. In low-income contexts, they are frequently the preferred option due to the high costs of DOACs. Its management is often challenging, and different digital health strategies have been implemented to support it.
Aims:
To systematically review the evidence on the impact of digital health strategies to support anticoagulation management compared to usual care on thromboembolic and bleeding events.
Methods:
Randomized controlled trials were searched in 5 databases from inception to September 2021. Two independent reviewers performed study selection, data extraction, and quality assessment using the Cochrane risk of bias tool (RoB2). Total thromboembolic events, major bleeding, mortality, and time in therapeutic range were assessed. Results were pooled using random effect models.
Results:
In total, 25 randomized controlled trials were included (25,746 patients) and classified as moderate to high risk of bias. Telemedicine resulted in a trend of reduced risk of thromboembolic events (13 studies, relative risk RR 0.75, 95% CI 0.53-1.07; I2=42%), comparable rates of major bleeding (11 studies, RR 0.94, 95% CI 0.82-1.07; I2=0%) and mortality (12 studies, RR 0.96, 95% CI 0.78-1.20; I2=11%), and an improved time in therapeutic range (16 studies, mean difference 3.38, 95% CI 1.12-5.65; I2=90%). In the subgroup of multitasking intervention, telemedicine resulted in an important reduction of thromboembolic events (RR 0.20, 95% CI 0.08-0.48).
Conclusions:
Digital health strategies resulted in similar rates of major bleeding and mortality, a trend for fewer thromboembolic events and better anticoagulation quality compared to standard care. Given the potential benefits of digital health-based care, such as greater access to remote populations, these findings may encourage further implementation of these strategies for anticoagulation management, particularly as part of multifaceted interventions for integrated care of chronic diseases.
Several pathologic processes might contribute to the degeneration of the cholinergic system in aging. We aimed to determine the contribution of amyloid, tau, and cerebrovascular biomarkers toward the ...degeneration of cholinergic white matter (WM) projections in cognitively unimpaired individuals.
The contribution of amyloid and tau pathology was assessed through CSF levels of the Aβ
ratio and phosphorylated tau (p-tau). CSF Aβ
levels were also measured. Cerebrovascular pathology was assessed using automatic segmentations of WM lesions (WMLs) on MRI. Cholinergic WM projections (i.e., cingulum and external capsule pathways) were modeled using tractography based on diffusion tensor imaging data. Sex and APOE ε4 carriership were also included in the analysis as variables of interest.
We included 203 cognitively unimpaired individuals from the H70 Gothenburg Birth Cohort Studies (all individuals aged 70 years, 51% female). WM lesion burden was the most important contributor to the degeneration of both cholinergic pathways (increase in mean square error IncMSE = 98.8% in the external capsule pathway and IncMSE = 93.3% in the cingulum pathway). Levels of Aβ
and p-tau also contributed to cholinergic WM degeneration, especially in the external capsule pathway (IncMSE = 28.4% and IncMSE = 23.4%, respectively). The Aβ
ratio did not contribute notably to the models (IncMSE<3.0%). APOE ε4 carriers showed poorer integrity in the cingulum pathway (IncMSE = 21.33%). Women showed poorer integrity of the external capsule pathway (IncMSE = 21.55%), which was independent of amyloid status as reflected by the nonsignificant differences in integrity when comparing amyloid-positive vs amyloid-negative women participants (T
= -1.55;
= 0.123).
In cognitively unimpaired older individuals, WMLs play a central role in the degeneration of cholinergic pathways. Our findings highlight the importance of WM lesion burden in the elderly population, which should be considered in the development of prevention programs for neurodegeneration and cognitive impairment.
The Cognitive Connectome in Healthy Aging Garcia-Cabello, Eloy; Gonzalez-Burgos, Lissett; Pereira, Joana B. ...
Frontiers in aging neuroscience,
08/2021, Letnik:
13
Journal Article
Recenzirano
Odprti dostop
Objectives
: Cognitive aging has been extensively investigated using both univariate and multivariate analyses. Sophisticated multivariate approaches such as graph theory could potentially capture ...unknown complex associations between multiple cognitive variables. The aim of this study was to assess whether cognition is organized into a structure that could be called the “cognitive connectome,” and whether such connectome differs between age groups.
Methods
: A total of 334 cognitively unimpaired individuals were stratified into early-middle-age (37–50 years,
n
= 110), late-middle-age (51–64 years,
n
= 106), and elderly (65–78 years,
n
= 118) groups. We built cognitive networks from 47 cognitive variables for each age group using graph theory and compared the groups using different global and nodal graph measures.
Results
: We identified a cognitive connectome characterized by five modules: verbal memory, visual memory—visuospatial abilities, procedural memory, executive—premotor functions, and processing speed. The elderly group showed reduced transitivity and average strength as well as increased global efficiency compared with the early-middle-age group. The late-middle-age group showed reduced global and local efficiency and modularity compared with the early-middle-age group. Nodal analyses showed the important role of executive functions and processing speed in explaining the differences between age groups.
Conclusions
: We identified a cognitive connectome that is rather stable during aging in cognitively healthy individuals, with the observed differences highlighting the important role of executive functions and processing speed. We translated the connectome concept from the neuroimaging field to cognitive data, demonstrating its potential to advance our understanding of the complexity of cognitive aging.
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