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Rho-family GTPases like RhoA and Rac-1 are potent regulators of cellular signaling that control gene expression, migration and inflammation. Activation of Rho-GTPases has been linked to podocyte dysfunction, a feature of chronic kidney diseases (CKD). We investigated the effect of Rac-1 and Rho kinase (ROCK) inhibition on progressive renal failure in mice and studied the underlying mechanisms in podocytes. SV129 mice were subjected to 5/6-nephrectomy which resulted in arterial hypertension and albuminuria. Subgroups of animals were treated with the Rac-1 inhibitor EHT1846, the ROCK inhibitor SAR407899 and the ACE inhibitor Ramipril. Only Ramipril reduced hypertension. In contrast, all inhibitors markedly attenuated albumin excretion as well as glomerular and tubulo-interstitial damage. The combination of SAR407899 and Ramipril was more effective in preventing albuminuria than Ramipril alone. To study the involved mechanisms, podocytes were cultured from SV129 mice and exposed to static stretch in the Flexcell device. This activated RhoA and Rac-1 and led via TGFβ to apoptosis and a switch of the cells into a more mesenchymal phenotype, as evident from loss of WT-1 and nephrin and induction of α-SMA and fibronectin expression. Rac-1 and ROCK inhibition as well as blockade of TGFβ dramatically attenuated all these responses. This suggests that Rac-1 and RhoA are mediators of podocyte dysfunction in CKD. Inhibition of Rho-GTPases may be a novel approach for the treatment of CKD.
Background The COVID-19 pandemic has spurred large-scale, inter-institutional research efforts. To enable these efforts, researchers must agree on dataset definitions that not only cover all elements relevant to the respective medical specialty but that are also syntactically and semantically interoperable. Following such an effort, the German Corona Consensus (GECCO) dataset has been developed previously as a harmonized, interoperable collection of the most relevant data elements for COVID-19-related patient research. As GECCO has been developed as a compact core dataset across all medical fields, the focused research within particular medical domains demands the definition of extension modules that include those data elements that are most relevant to the research performed in these individual medical specialties.
Objective To (i) specify a workflow for the development of interoperable dataset definitions that involves a close collaboration between medical experts and information scientists and to (ii) apply the workflow to develop dataset definitions that include data elements most relevant to COVID-19-related patient research in immunization, pediatrics, and cardiology.
Methods We developed a workflow to create dataset definitions that are (i) content-wise as relevant as possible to a specific field of study and (ii) universally usable across computer systems, institutions, and countries, i.e., interoperable. We then gathered medical experts from three specialties (immunization, pediatrics, and cardiology) to the select data elements most relevant to COVID-19-related patient research in the respective specialty. We mapped the data elements to international standardized vocabularies and created data exchange specifications using HL7 FHIR. All steps were performed in close interdisciplinary collaboration between medical domain experts and medical information scientists. The profiles and vocabulary mappings were syntactically and semantically validated in a two-stage process.
Results We created GECCO extension modules for the immunization, pediatrics, and cardiology domains with respect to the pandemic requests. The data elements included in each of these modules were selected according to the here developed consensus-based workflow by medical experts from the respective specialty to ensure that the contents are aligned with the respective research needs. We defined dataset specifications for a total number of 48 (immunization), 150 (pediatrics), and 52 (cardiology) data elements that complement the GECCO core dataset. We created and published implementation guides and example implementations as well as dataset annotations for each extension module.
Conclusions These here presented GECCO extension modules, which contain data elements most relevant to COVID-19-related patient research in immunization, pediatrics and cardiology, were defined in an interdisciplinary, iterative, consensus-based workflow that may serve as a blueprint for the development of further dataset definitions. The GECCO extension modules provide a standardized and harmonized definition of specialty-related datasets that can help to enable inter-institutional and cross-country COVID-19 research in these specialties.
Based on Eysenck’s pioneering work, CNS arousal has long been considered an encouraging biological candidate that may explain individual differences in human personality. Yet, results from empirical studies remained inconclusive. Notably, the vast majority of published results have been derived from small samples, and EEG alpha power has usually served as exclusive indicator for CNS arousal. In this study, we selected N = 468 individuals of the LIFE-Adult cohort and investigated the associations between the Big Five personality traits and CNS arousal by using the low-resolution electromagnetic tomography-based analysis tool VIGALL. Our analyses revealed that subjects who reported higher levels of extraversion and openness to experience, respectively, exhibited lower levels of CNS arousal in the resting state. Bayesian and frequentist analysis results were especially convincing for openness to experience. Among the lower-order personality traits, we obtained strongest evidence for neuroticism facet ‘impulsivity’ and reduced CNS arousal. We regard these findings as well in line with the postulations of Eysenck and Zuckerman and consistent with the assumptions of the ‘arousal regulation model’. Our results also agree with meta-analytically derived effect sizes in the field of individual differences research, highlighting the need for large studies with at least several hundreds of subjects.
Highlights
• A big dataset reveals age-related alterations in EEG biomarkers and cognition.
• Prominent decline of individual alpha peak frequency primarily in temporal lobes.
• A positive association between individual alpha peak frequency and working memory.
• Absence of age-related alpha power decline when controlling for 1/f decay of the PSD.
• Alpha power is negatively associated with the speed of processing in elderly sample.
Abstract
While many structural and biochemical changes in the brain have previously been associated with older age, findings concerning functional properties of neuronal networks, as reflected in their electrophysiological signatures, remain rather controversial. These discrepancies might arise due to several reasons, including diverse factors determining general spectral slowing in the alpha frequency range as well as amplitude mixing between the rhythmic and non-rhythmic parameters. We used a large dataset (N = 1703, mean age 70) to comprehensively investigate age-related alterations in multiple EEG biomarkers taking into account rhythmic and non-rhythmic activity and their individual contributions to cognitive performance. While we found strong evidence for an individual alpha peak frequency (IAF) decline in older age, we did not observe a significant relationship between theta power and age while controlling for IAF. Not only did IAF decline with age, but it was also positively associated with interference resolution in a working memory task primarily in the right and left temporal lobes suggesting its functional role in information sampling. Critically, we did not detect a significant relationship between alpha power and age when controlling for the 1/f spectral slope, while the latter one showed age-related alterations. These findings thus suggest that the entanglement of IAF slowing and power in the theta frequency range, as well as 1/f slope and alpha power measures, might explain inconsistencies reported previously in the literature. Finally, despite the absence of age-related alterations, alpha power was negatively associated with the speed of processing in the right frontal lobe while 1/f slope showed no consistent relationship to cognitive performance. Our results thus demonstrate that multiple electrophysiological features, as well as their interplay, should be considered for the comprehensive assessment of association between age, neuronal activity, and cognitive performance.
Background: The COVID-19 pandemic has spurred large-scale, inter-institutional research efforts. To enable these efforts, the German Corona Consensus (GECCO) dataset has been developed previously as a harmonized, interoperable collection of the most relevant data elements for COVID-19-related patient research. As GECCO has been developed as a compact core dataset across all medical fields, the focused research within particular medical domains demanded the definition of extension modules that include those data elements that are most relevant to the research performed in these individual medical specialties.
Main body: We created GECCO extension modules for the immunization, pediatrics, and cardiology domains with respect to the pandemic requests. The data elements included in each of these modules were selected in a consensus-based process by working groups of medical experts from the respective specialty to ensure that the contents are aligned with the research needs of the specialty. The selected data elements were mapped to international standardized vocabularies and data exchange specifications were created using HL7 FHIR profiles on the appropriate resources. All steps were performed in close interdisciplinary collaboration between medical domain experts, medical information scientists and FHIR developers. The profiles and vocabulary mappings were syntactically and semantically validated in a two-stage process. In that way, we defined dataset specifications for a total number of 23 (immunization), 59 (pediatrics), and 50 (cardiology) data elements that augment the GECCO core dataset. We created and published implementation guides and example implementations as well as dataset annotations for each extension module.
Conclusions: We here present extension modules for the GECCO core dataset that contain data elements most relevant to COVID-19-related patient research in immunization, pediatrics and cardiology. These extension modules were defined in an interdisciplinary, iterative, consensus-based approach that may serve as a blueprint for the development of further dataset definitions and GECCO extension modules. The here developed GECCO extension modules provide a standardized and harmonized definition of specialty-related datasets that can help to enable inter-institutional and cross-country COVID-19 research in these specialties.
Relationship between regional white matter hyperintensities and alpha oscillations in older adults
(2021)
Aging is associated with increased white matter hyperintensities (WMHs) and with the alterations of alpha oscillations (7–13 Hz). However, a crucial question remains, whether changes in alpha oscillations relate to aging per se or whether this relationship is mediated by age-related neuropathology like WMHs. Using a large cohort of cognitively healthy older adults (N=907, 60-80 years), we assessed relative alpha power, alpha peak frequency, and long-range temporal correlations (LRTC) from resting-state EEG. We further associated these parameters with voxel-wise WMHs from 3T MRI. We found that a higher prevalence of WMHs in the superior and posterior corona radiata as well as in the thalamic radiation was related to elevated alpha power, with the strongest association in the bilateral occipital cortex. In contrast, we observed no significant relation of the WMHs probability with alpha peak frequency and LRTC. Finally, higher age was associated with elevated alpha power via total WMH volume. Although an increase in alpha oscillations due to WMH can have a compensatory nature, we rather suggest that an elevated alpha power is a consequence of WMH affecting a spatial organization of alpha sources.
Central nervous hyperarousal is as a key component of current pathophysiological concepts of chronic insomnia disorder. However, there are still open questions regarding its exact nature and the mechanisms linking hyperarousal to sleep disturbance. Here, we aimed at studying waking state hyperarousal in insomnia by the perspective of resting-state vigilance dynamics. The VIGALL (Vigilance Algorithm Leipzig) algorithm has been developed to investigate resting-state vigilance dynamics, and it revealed, for example, enhanced vigilance stability in depressive patients. We hypothesized that patients with insomnia also show a more stable vigilance regulation. Thirty-four unmedicated patients with chronic insomnia and 25 healthy controls participated in a twenty-minute resting-state electroencephalography (EEG) measurement following a night of polysomnography. Insomnia patients showed enhanced EEG vigilance stability as compared to controls. The pattern of vigilance hyperstability differed from that reported previously in depressive patients. Vigilance hyperstability was also present in insomnia patients showing only mildly reduced sleep efficiency. In this subgroup, vigilance hyperstability correlated with measures of disturbed sleep continuity and arousal. Our data indicate that insomnia disorder is characterized by hyperarousal at night as well as during daytime.
Relationship between regional white matter hyperintensities and alpha oscillations in older adults
(2020)
White matter hyperintensities (WMHs) in the cerebral white matter and attenuation of alpha oscillations (AO; 7–13 Hz) occur with the advancing age. However, a crucial question remains, whether changes in AO relate to aging per se or they rather reflect the impact of age-related neuropathology like WMHs. In this study, using a large cohort (N=907) of elderly participants (60-80 years), we assessed relative alpha power (AP), individual alpha peak frequency (IAPF) and long-range temporal correlations (LRTC) from resting-state EEG. We further associated these parameters with voxel-wise WMHs from 3T MRI. We found that higher prevalence of WMHs in the superior and posterior corona radiata was related to elevated relative AP, with strongest correlations in the bilateral occipital cortex, even after controlling for potential confounding factors. In contrast, we observed no significant relation of probability of WMH occurrence with IAPF and LRTC. We argue that the WMH-associated increase of AP reflects generalized and likely compensatory changes of AO leading to a larger number of synchronously recruited neurons.
Relationship between regional white matter hyperintensities and alpha oscillations in older adults
(2020)
Objective: To investigate whether regional white matter hyperintensities (WMHs) relate to alpha oscillations (AO) in a large population-based sample of elderly individuals.
Methods: We associated voxel-wise WMHs from high-resolution 3-Tesla MRI with neuronal alpha oscillations (AO) from resting-state multichannel EEG at sensor (N=907) and source space (N=855) in older participants of the LIFE-Adult study (60–80 years). In EEG, we computed relative alpha power (AP), individual alpha peak frequency (IAPF), as well as long-range temporal correlations (LRTC) that represent dynamic properties of the signal. We implemented whole-brain voxel-wise regression models to identify regions where parameters of AO were linked to probability of WMH occurrence. We further used mediation analyses to examine whether WMH volume mediated the relationship between age and AO.
Results: Higher prevalence of WMHs in the superior and posterior corona radiata was related to elevated relative AP, with strongest correlations in the bilateral occipital cortex, even after controlling for potential confounding factors. The age-related increase of relative AP in the right temporal brain region was shown to be mediated by total WMH volume.
Conclusion: A high relative AP corresponding to increased regional WMHs was not associated with age per se, in fact, this relationship was mediated by WMHs. We argue that the WMH-associated increase of AP reflects a generalized and likely compensatory spread of AO leading to a larger number of synchronously recruited neurons. Our findings thus suggest that longitudinal EEG recordings might be sensitive to detect functional changes due to WMHs.