34 research outputs found
Mechanotransductive feedback control of endothelial cell motility and vascular morphogenesis
Vascular morphogenesis requires persistent endothelial cell motility that is responsive to diverse and dynamic mechanical stimuli. Here, we interrogated the mechanotransductive feedback dynamics that govern endothelial cell motility and vascular morphogenesis. We show that the transcriptional regulators, YAP and TAZ, are activated by mechanical cues to transcriptionally limit cytoskeletal and focal adhesion maturation, forming a conserved mechanotransductive feedback loop that mediates human endothelial cell motility in vitro and zebrafish intersegmental vessel (ISV) morphogenesis in vivo. This feedback loop closes in 4 hours, achieving cytoskeletal equilibrium in 8 hours. Feedback loop inhibition arrested endothelial cell migration in vitro and ISV morphogenesis in vivo. Inhibitor washout at 3 hrs, prior to feedback loop closure, restored vessel growth, but washout at 8 hours, longer than the feedback timescale, did not, establishing lower and upper bounds for feedback kinetics in vivo. Mechanistically, YAP and TAZ induced transcriptional suppression of myosin II activity to maintain dynamic cytoskeletal equilibria. Together, these data establish the mechanoresponsive dynamics of a transcriptional feedback loop necessary for persistent endothelial cell migration and vascular morphogenesis
Business networks and localization effects for new Swedish technology-based firms’ innovation performance
This study examines the business networks and localization effects for new technology-based firms (NTBFs) in the context of innovation performance (the number of patents and product differentiation). In this regard, the study includes 28 variables. A survey was conducted in 2016 with 401 Swedish NTBFs that were small and young (the employment mean was 1.80 and the average age of each firm was 28.3\ua0months). The biggest category of NTBFs was knowledge-intensive high-technology services, followed by medium high-technology manufacturing, and high-technology manufacturing. Hypotheses on how business networks and localization are related to innovation performance were tested using principal component analysis, correlation analysis, and regression analysis. The results show that the primary significant factor for innovation performance regarding business networks and localization dimensions are professional network services, while industrial and regional areas also have a positive relationship on product differentiation. Our study also shows that innovation performance enhances firms’ abilities to access external financing through professional network services (e.g., venture capital companies)
Factors associated with adverse COVID-19 outcomes in patients with psoriasis-insights from a global registry-based study.
BACKGROUND: The multimorbid burden and use of systemic immunosuppressants in people with psoriasis may confer greater risk of adverse outcomes of coronavirus disease 2019 (COVID-19), but the data are limited. OBJECTIVE: Our aim was to characterize the course of COVID-19 in patients with psoriasis and identify factors associated with hospitalization. METHODS: Clinicians reported patients with psoriasis with confirmed/suspected COVID-19 via an international registry, Psoriasis Patient Registry for Outcomes, Therapy and Epidemiology of COVID-19 Infection. Multiple logistic regression was used to assess the association between clinical and/or demographic characteristics and hospitalization. A separate patient-facing registry characterized risk-mitigating behaviors. RESULTS: Of 374 clinician-reported patients from 25 countries, 71% were receiving a biologic, 18% were receiving a nonbiologic, and 10% were not receiving any systemic treatment for psoriasis. In all, 348 patients (93%) were fully recovered from COVID-19, 77 (21%) were hospitalized, and 9 (2%) died. Increased hospitalization risk was associated with older age (multivariable-adjusted odds ratio [OR] = 1.59 per 10 years; 95% CI = 1.19-2.13), male sex (OR = 2.51; 95% CI = 1.23-5.12), nonwhite ethnicity (OR = 3.15; 95% CI = 1.24-8.03), and comorbid chronic lung disease (OR = 3.87; 95% CI = 1.52-9.83). Hospitalization was more frequent in patients using nonbiologic systemic therapy than in those using biologics (OR = 2.84; 95% CI = 1.31-6.18). No significant differences were found between classes of biologics. Independent patient-reported data (n = 1626 across 48 countries) suggested lower levels of social isolation in individuals receiving nonbiologic systemic therapy than in those receiving biologics (OR = 0.68; 95% CI = 0.50-0.94). CONCLUSION: In this international case series of patients with moderate-to-severe psoriasis, biologic use was associated with lower risk of COVID-19-related hospitalization than with use of nonbiologic systemic therapies; however, further investigation is warranted on account of potential selection bias and unmeasured confounding. Established risk factors (being older, being male, being of nonwhite ethnicity, and having comorbidities) were associated with higher hospitalization rates
TRY plant trait database – enhanced coverage and open access
Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
The genetic architecture of the human cerebral cortex
The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder
Quantitative 18F-AV1451 Brain Tau PET Imaging in Cognitively Normal Older Adults, Mild Cognitive Impairment, and Alzheimer's Disease Patients
Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p < 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p > 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification
Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images
Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease
Recommended from our members
Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis
Multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD–abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system's integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions