Endothelial cell junctions and the regulation of vascular permeability and leukocyte transmigration

The endothelial lining of the vasculature forms the physical barrier between the blood and underlying tissues. Junctions between adjacent endothelial cells are dynamically modulated to sustain vascular homeostasis and to support the transendothelial migration of leukocytes during inflammation. A variety of factors initiate intracellular signaling pathways which regulate the opening and resealing of junctional complexes. This review focuses on three primary signaling pathways initiated within endothelial cells by the binding of vasoactive factors and leukocyte adhesion: Rho GTPases, reactive oxygen species, and tyrosine phosphorylation of junctional proteins. These pathways converge to regulate junctional permeability, either by affecting the stability of junctional proteins or by modulating their interactions. Although much progress has been made in understanding the relationships of these pathways, many questions remain to be answered. A full understanding of the signaling cascades that affect endothelial junctions should identify novel therapeutic targets for diseases that involve excessive permeability or inappropriate leukocyte infiltration into tissues

A Deep-Learning Algorithm to Predict Short-Term Progression to Geographic Atrophy on Spectral-Domain Optical Coherence Tomography

IMPORTANCE: The identification of patients at risk of progressing from intermediate age-related macular degeneration (iAMD) to geographic atrophy (GA) is essential for clinical trials aimed at preventing disease progression. DeepGAze is a fully automated and accurate convolutional neural network-based deep learning algorithm for predicting progression from iAMD to GA within 1 year from spectral-domain optical coherence tomography (SD-OCT) scans. OBJECTIVE: To develop a deep-learning algorithm based on volumetric SD-OCT scans to predict the progression from iAMD to GA during the year following the scan. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study included participants with iAMD at baseline and who either progressed or did not progress to GA within the subsequent 13 months. Participants were included from centers in 4 US states. Data set 1 included patients from the Age-Related Eye Disease Study 2 AREDS2 (Ancillary Spectral-Domain Optical Coherence Tomography) A2A study (July 2008 to August 2015). Data sets 2 and 3 included patients with imaging taken in routine clinical care at a tertiary referral center and associated satellites between January 2013 and January 2023. The stored imaging data were retrieved for the purpose of this study from July 1, 2022, to February 1, 2023. Data were analyzed from May 2021 to July 2023. EXPOSURE: A position-aware convolutional neural network with proactive pseudointervention was trained and cross-validated on Bioptigen SD-OCT volumes (data set 1) and validated on 2 external data sets comprising Heidelberg Spectralis SD-OCT scans (data sets 2 and 3). MAIN OUTCOMES AND MEASURES: Prediction of progression to GA within 13 months was evaluated with area under the receiver-operator characteristic curves (AUROC) as well as area under the precision-recall curve (AUPRC), sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. RESULTS: The study included a total of 417 patients: 316 in data set 1 (mean [SD] age, 74 [8]; 185 [59%] female), 53 in data set 2, (mean [SD] age, 83 [8]; 32 [60%] female), and 48 in data set 3 (mean [SD] age, 81 [8]; 32 [67%] female). The AUROC for prediction of progression from iAMD to GA within 1 year was 0.94 (95% CI, 0.92-0.95; AUPRC, 0.90 [95% CI, 0.85-0.95]; sensitivity, 0.88 [95% CI, 0.84-0.92]; specificity, 0.90 [95% CI, 0.87-0.92]) for data set 1. The addition of expert-annotated SD-OCT features to the model resulted in no improvement compared to the fully autonomous model (AUROC, 0.95; 95% CI, 0.92-0.95; P = .19). On an independent validation data set (data set 2), the model predicted progression to GA with an AUROC of 0.94 (95% CI, 0.91-0.96; AUPRC, 0.92 [0.89-0.94]; sensitivity, 0.91 [95% CI, 0.74-0.98]; specificity, 0.80 [95% CI, 0.63-0.91]). At a high-specificity operating point, simulated clinical trial recruitment was enriched for patients progressing to GA within 1 year by 8.3- to 20.7-fold (data sets 2 and 3). CONCLUSIONS AND RELEVANCE: The fully automated, position-aware deep-learning algorithm assessed in this study successfully predicted progression from iAMD to GA over a clinically meaningful time frame. The ability to predict imminent GA progression could facilitate clinical trials aimed at preventing the condition and could guide clinical decision-making regarding screening frequency or treatment initiation

Prime movers : mechanochemistry of mitotic kinesins

Mitotic spindles are self-organizing protein machines that harness teams of multiple force generators to drive chromosome segregation. Kinesins are key members of these force-generating teams. Different kinesins walk directionally along dynamic microtubules, anchor, crosslink, align and sort microtubules into polarized bundles, and influence microtubule dynamics by interacting with microtubule tips. The mechanochemical mechanisms of these kinesins are specialized to enable each type to make a specific contribution to spindle self-organization and chromosome segregation

Processive Movement by a Kinesin Heterodimer with an Inactivating Mutation in One Head†

ABSTRACT: A single molecule of the motor enzyme kinesin-1 keeps a tight grip on its microtubule track, making tens or hundreds of discrete, unidirectional 8 nm steps before dissociating. This high duty ratio processive movement is thought to require a mechanism in which alternating stepping of the two head domains of the kinesin dimer is driven by alternating, overlapped cycles of ATP hydrolysis by the two heads. The R210K point mutation in Drosophila kinesin heavy chain was reported to disrupt the ability of the enzyme active site to catalyze ATP P-O bond cleavage. We expressed R210K homodimers as well as isolated R210K heads and confirmed that both are essentially inactive. We then coexpressed tagged R210K subunits with untagged wild-type subunits and affinity purified R210K/wild-type heterodimers together with the inactive R210K homodimers. In contrast to the R210K head or homodimer, the heterodimer was a highly active (>50 % of wild-type) microtubule-stimulated ATPase, and the heterodimer displayed high duty ratio processive movement in single-molecule motility experiments. Thus, dimerization of a subunit containing the inactivating mutation with a functional subunit can complement the mutation; this must occur either by lowering or by bypassing kinetic barriers in the ATPase or mechanical cycles of the mutant head. The observations provide support for kinesin-1 gating mechanisms in which one head stimulates the rate of essential processes in the other

Focal segmental glomerulosclerosis, Coats’-like retinopathy, sensorineural deafness and chromosome 4 duplication: a new association

We describe the novel association in a girl of nephrotic syndrome due to focal segmental glomerulosclerosis, bilateral sensorineural deafness, basal ganglia calcification, bilateral retinopathy similar to that seen in Coats’ disease, with de novo duplication of a subtelomeric region of chromosome 4q35. The chromosomal duplication was identified during investigation of a possible association with features of fascio-scapulo-humeral dystrophy (FSHD). This duplication has not previously been reported with FSGS and adds to the expanding number of genetic associations with steroid-resistant nephrotic syndrome

Does the sole description of a tax authority affect tax evasion? The impact of described coercive and legitimate power.

Following the classic economic model of tax evasion, taxpayers base their tax decisions on economic determinants, like fine rate and audit probability. Empirical findings on the relationship between economic key determinants and tax evasion are inconsistent and suggest that taxpayers may rather rely on their beliefs about tax authority’s power. Descriptions of the tax authority’s power may affect taxpayers’ beliefs and as such tax evasion. Experiment 1 investigates the impact of fines and beliefs regarding tax authority’s power on tax evasion. Experiments 2-4 are conducted to examine the effect of varying descriptions about a tax authority’s power on participants’ beliefs and respective tax evasion. It is investigated whether tax evasion is influenced by the description of an authority wielding coercive power (Experiment 2), legitimate power (Experiment 3), and coercive and legitimate power combined (Experiment 4). Further, it is examined whether a contrast of the description of power (low to high power; high to low power) impacts tax evasion (Experiments 2-4). Results show that the amount of fine does not impact tax payments, whereas participants’ beliefs regarding tax authority’s power significantly shape compliance decisions. Descriptions of high coercive power as well as high legitimate power affect beliefs about tax authority’s power and positively impact tax honesty. This effect still holds if both qualities of power are applied simultaneously. The contrast of descriptions has little impact on tax evasion. The current study indicates that descriptions of the tax authority, e.g., in information brochures and media reports, have more influence on beliefs and tax payments than information on fine rates. Methodically, these considerations become particularly important when descriptions or vignettes are used besides objective information