Scientific Reports

Journal: Scientific Reports

Abbreviation

Sci Rep

Publisher

Macmillan Publishers

ISSN

2045-2322

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Publications 1 - 10 of 59

Pupil dilation predicts individual self-regulation success across domains
Maier, Silvia U.; Grueschow, Marcus (2021)
Scientific Reports
Multiple theories have proposed that increasing central arousal through the brain’s locus coeruleus—norepinephrine system may facilitate cognitive control and memory. However, the role of the arousal system in emotion regulation is less well understood. Pupil diameter is a proxy to infer upon the central arousal state. We employed an emotion regulation paradigm with a combination of design features that allowed us to dissociate regulation from emotional arousal in the pupil diameter time course of 34 healthy adults. Pupil diameter increase during regulation predicted individual differences in emotion regulation success beyond task difficulty. Moreover, the extent of this individual regulatory arousal boost predicted performance in another self-control task, dietary health challenges. Participants who harnessed more regulation-associated arousal during emotion regulation were also more successful in choosing healthier foods. These results suggest that a common arousal-based facilitation mechanism may support an individual’s self-control across domains.
Morphometric analysis of spread platelets identifies integrin αIIbβ3-specific contractile phenotype
Lickert, Sebastian; Sorrentino, Simona; Studt, Jan-Dirk; et al. (2018)
Scientific Reports
Predicting glaucoma progression using deep learning framework guided by generative algorithm
Hussain, Shaista; Chua, Jacqueline; Wong, Damon; et al. (2023)
Scientific Reports
Glaucoma is a slowly progressing optic neuropathy that may eventually lead to blindness. To help patients receive customized treatment, predicting how quickly the disease will progress is important. Structural assessment using optical coherence tomography (OCT) can be used to visualize glaucomatous optic nerve and retinal damage, while functional visual field (VF) tests can be used to measure the extent of vision loss. However, VF testing is patient-dependent and highly inconsistent, making it difficult to track glaucoma progression. In this work, we developed a multimodal deep learning model comprising a convolutional neural network (CNN) and a long short-term memory (LSTM) network, for glaucoma progression prediction. We used OCT images, VF values, demographic and clinical data of 86 glaucoma patients with five visits over 12 months. The proposed method was used to predict VF changes 12 months after the first visit by combining past multimodal inputs with synthesized future images generated using generative adversarial network (GAN). The patients were classified into two classes based on their VF mean deviation (MD) decline: slow progressors (< 3 dB) and fast progressors (> 3 dB). We showed that our generative model-based novel approach can achieve the best AUC of 0.83 for predicting the progression 6 months earlier. Further, the use of synthetic future images enabled the model to accurately predict the vision loss even earlier (9 months earlier) with an AUC of 0.81, compared to using only structural (AUC = 0.68) or only functional measures (AUC = 0.72). This study provides valuable insights into the potential of using synthetic follow-up OCT images for early detection of glaucoma progression.
Auxetic structures used in kinesiology tapes can improve form-fitting and personalization
Meeusen, Luna; Candidori, Sara; Micoli, Laura Loredana; et al. (2022)
Scientific Reports
Each year 65% of young athletes and 25% of physically active adults suffer from at least one musculoskeletal injury that prevents them from continuing with physical activity, negatively influencing their physical and mental well-being. The treatment of musculoskeletal injuries with the adhesive elastic kinesiology tape (KT) decreases the recovery time. Patients can thus recommence physical exercise earlier. Here, a novel KT based on auxetic structures is proposed to simplify the application procedure and allow personalization. This novel KT exploits the form-fitting property of auxetics as well as their ability to simultaneously expand in two perpendicular directions when stretched. The auxetic contribution is tuned by optimizing the structure design using analytical equations and experimental measurements. A reentrant honeycomb topology is selected to demonstrate the validity of the proposed approach. Prototypes of auxetic KT to treat general elbow pains and muscle tenseness in the forearm are developed.
Adaptive changes in sensorimotor processing in patients with acute low back pain
Boendermaker, Bart; Buechler, Roman; Michels, Lars; et al. (2022)
Scientific Reports
In low back pain (LBP), primary care and secondary prevention of recurrent and persistent LBP are not always successful. Enhanced understanding of neural mechanisms of sensorimotor processing and pain modulation in patients with acute LBP is mandatory. This explorative fMRI study investigated sensorimotor processing due to mechanosensory stimulation of the lumbar spine. We studied 19 adult patients with acute LBP (< 4 weeks of an acute episode) and 23 healthy controls. On a numeric rating scale, patients reported moderate mean pain intensity of 4.5 out of 10, while LBP-associated disability indicated mild mean disability. The event-related fMRI analysis yielded no between-group differences. However, the computation of functional connectivity resulted in adaptive changes in networks involved in sensorimotor processing in the patient group: Connectivity strength was decreased in the salience and cerebellar networks but increased in the limbic and parahippocampal networks. Timewise, these results indicate that early connectivity changes might reflect adaptive physiological processes in an episode of acute LBP. These findings raise intriguing questions regarding their role in pain persistence and recurrences of LBP, particularly concerning the multiple consequences of acute LBP pain. Advanced understanding of neural mechanisms of processing non-painful mechanosensations in LBP may also improve therapeutic approaches.
Self-regulation of visual word form area activation with real-time fMRI neurofeedback
Haugg, Amelie; Frei, Nada; Menghini, Milena; et al. (2023)
Scientific Reports
The Visual Word Form Area (VWFA) is a key region of the brain’s reading network and its activation has been shown to be strongly associated with reading skills. Here, for the first time, we investigated whether voluntary regulation of VWFA activation is feasible using real-time fMRI neurofeedback. 40 adults with typical reading skills were instructed to either upregulate (UP group, N = 20) or downregulate (DOWN group, N = 20) their own VWFA activation during six neurofeedback training runs. The VWFA target region was individually defined based on a functional localizer task. Before and after training, also regulation runs without feedback (“no-feedback runs”) were performed. When comparing the two groups, we found stronger activation across the reading network for the UP than the DOWN group. Further, activation in the VWFA was significantly stronger in the UP group than the DOWN group. Crucially, we observed a significant interaction of group and time (pre, post) for the no-feedback runs: The two groups did not differ significantly in their VWFA activation before neurofeedback training, but the UP group showed significantly stronger activation than the DOWN group after neurofeedback training. Our results indicate that upregulation of VWFA activation is feasible and that, once learned, successful upregulation can even be performed in the absence of feedback. These results are a crucial first step toward the development of a potential therapeutic support to improve reading skills in individuals with reading impairments.
A realistic morpho-anatomical connection strategy for modelling full-scale point-neuron microcircuits
Gandolfi, Daniela; Mapelli, Jonathan; Solinas, Sergio; et al. (2022)
Scientific Reports
The modeling of extended microcircuits is emerging as an effective tool to simulate the neurophysiological correlates of brain activity and to investigate brain dysfunctions. However, for specific networks, a realistic modeling approach based on the combination of available physiological, morphological and anatomical data is still an open issue. One of the main problems in the generation of realistic networks lies in the strategy adopted to build network connectivity. Here we propose a method to implement a neuronal network at single cell resolution by using the geometrical probability volumes associated with pre- and postsynaptic neurites. This allows us to build a network with plausible connectivity properties without the explicit use of computationally intensive touch detection algorithms using full 3D neuron reconstructions. The method has been benchmarked for the mouse hippocampus CA1 area, and the results show that this approach is able to generate full-scale brain networks at single cell resolution that are in good agreement with experimental findings. This geometric reconstruction of axonal and dendritic occupancy, by effectively reflecting morphological and anatomical constraints, could be integrated into structured simulators generating entire circuits of different brain areas facilitating the simulation of different brain regions with realistic models.
Flow and wake characteristics associated with large wood to inform river restoration
Schalko, Isabella; Wohl, Ellen; Nepf, Heidi M. (2021)
Scientific Reports
Wood is an integral part of a river ecosystem and the number of restoration projects using log placements is increasing. Physical model tests were used to explore how the wood position and submergence level (discharge) affect wake structure, and hence the resulting habitat. We observed a von-Kármán vortex street (VS) for emergent logs placed at the channel center, while no VS formed for submerged logs, because the flow entering the wake from above the log (sweeping flow) inhibited VS formation. As a result, emergent logs placed at the channel center resulted in ten times higher turbulent kinetic energy compared to submerged logs. In addition, both spatial variation in time-mean velocity and turbulence level increased with increasing log length and decreasing submergence level. Submerged logs and logs placed at the channel side created a greater velocity deficit and a longer recirculation zone, both of which can increase the residence time in the wake and deposition of organic matter and nutrients. The results demonstrate that variation in log size and degree of submergence can be used as a tool to vary habitat suitability for different fish preferences. To maximize habitat diversity in rivers, we suggest a diverse large wood placement.
Functional connectivity and amplitude of low-frequency fluctuations changes in people with complete subacute and chronic spinal cord injury
Vallesi, Vanessa; Richter, Johannes K.; Hunkeler, Nadine; et al. (2022)
Scientific Reports
After spinal cord injury (SCI), reorganization processes and changes in brain connectivity occur. Besides the sensorimotor cortex, the subcortical areas are strongly involved in motion and executive control. This exploratory study focusses on the cerebellum and vermis. Resting-state functional magnetic resonance imaging (fMRI) was performed. Between-group differences were computed using analysis of covariance and post-hoc tests for the seed-based connectivity measure with vermis and cerebellum as regions of interest. Twenty participants with complete SCI (five subacute SCI, 15 with chronic SCI) and 14 healthy controls (HC) were included. Functional connectivity (FC) was lower in all subjects with SCI compared with HC in vermis IX, right superior frontal gyrus (pFDR = 0.008) and right lateral occipital cortex (pFDR = 0.036). In addition, functional connectivity was lower in participants with chronic SCI compared with subacute SCI in bilateral cerebellar crus I, left precentral- and middle frontal gyrus (pFDR = 0.001). Furthermore, higher amplitude of low-frequency fluctuations (ALFF) was found in the left thalamus in individuals with subacute SCI (pFDR = 0.002). Reduced FC in SCI indicates adaptation with associated deficit in sensory and motor function. The increased ALFF in subacute SCI might reflect reorganization processes in the subacute phase.
CT-based comparison of porcine, ovine, and human pulmonary arterial morphometry
Goubergrits, Leonid; Schafstedde, Marie; Cesarovic, Nikola; et al. (2023)
Scientific Reports
To facilitate pre-clinical animal and in-silico clinical trials for implantable pulmonary artery pressure sensors, understanding the respective species pulmonary arteries (PA) anatomy is important. Thus, morphological parameters describing PA of pigs and sheep, which are common animal models, were compared with humans. Retrospective computed tomography data of 41 domestic pigs (82.6 ± 18.8 kg), 14 sheep (49.1 ± 6.9 kg), and 49 patients (76.8 ± 18.2 kg) were used for reconstruction of the subject-specific PA anatomy. 3D surface geometries including main, left, and right PA as well as LPA and RPA side branches were manually reconstructed. Then, specific geometric parameters (length, diameters, taper, bifurcation angle, curvature, and cross-section enlargement) affecting device implantation and post-interventional device effect and efficacy were automatically calculated. For both animal models, significant differences to the human anatomy for most geometric parameters were found, even though the respective parameters’ distributions also featured relevant overlap. Out of the two animal models, sheep seem to be better suitable for a preclinical study when considering only PA morphology. Reconstructed geometries are provided as open data for future studies. These findings support planning of preclinical studies and will help to evaluate the results of animal trials.

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