The Proposed Constitutional Amendments to the Local Finance Article: A Critical Analysis

This paper examines the recent proposals of the Committee on Municipal Affairs of the Association of the Bar of the City of New York to amend Article VIII of the New York State Constitution. These amendments would modify the powers of local governments to raise and spend money. The paper considers philosophical, political and judicial theories of local finance, and summarizes the effects of the proposals, concluding that they have merit and should be explored

Reproducibility of in-vivo OCT measured three-dimensional human lamina cribrosa microarchitecture

Purpose: To determine the reproducibility of automated segmentation of the three-dimensional (3D) lamina cribrosa (LC) microarchitecture scanned in-vivo using optical coherence tomography (OCT). Methods: Thirty-nine eyes (8 healthy, 19 glaucoma suspects and 12 glaucoma) from 49 subjects were scanned twice using swept-source (SS-) OCT in a 3.5x3.5x3.64 mm (400x400x896 pixels) volume centered on the optic nerve head, with the focus readjusted after each scan. The LC was automatically segmented and analyzed for microarchitectural parameters, including pore diameter, pore diameter standard deviation (SD), pore aspect ratio, pore area, beam thickness, beam thickness SD, and beam thickness to pore diameter ratio. Reproducibility of the parameters was assessed by computing the imprecision of the parameters between the scans. Results: The automated segmentation demonstrated excellent reproducibility. All LC microarchitecture parameters had an imprecision of less or equal to 4.2%. There was little variability in imprecision with respect to diagnostic category, although the method tends to show higher imprecision amongst healthy subjects. Conclusion: The proposed automated segmentation of the LC demonstrated high reproducibility for 3D LC parameters. This segmentation analysis tool will be useful for in-vivo studies of the LC. © 2014 Wang et al

Neuroimaging-Based Classification of PTSD Using Data-Driven Computational Approaches:A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality.RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60% test AUC for s-MRI, 59% for rs-fMRI and 56% for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75% AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance.CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.</p

Omicron extensively but incompletely escapes Pfizer BNT162b2 neutralization

The emergence of Omicron (Pango lineage B.1.1.529), first identified in Botswana and South Africa, may compromise vaccine effectiveness and lead to re-infections1. We investigated whether Omicron escapes antibody neutralization in South Africans vaccinated with Pfizer BNT162b2. We also investigated if Omicron requires the ACE2 receptor to infect cells. We isolated and sequence confirmed live Omicron virus from an infected person in South Africa and compared plasma neutralization of Omicron relative to an ancestral SARS-CoV-2 strain, observing that Omicron still required ACE2 to infect. For neutralization, blood samples were taken soon after vaccination from participants who were vaccinated and previously infected or vaccinated with no evidence of previous infection. Neutralization of ancestral virus was much higher in infected and vaccinated versus vaccinated only participants but both groups showed a 22-fold escape from vaccine elicited neutralization by the Omicron variant. However, in the previously infected and vaccinated group, the level of residual neutralization of Omicron was similar to the level of neutralization of ancestral virus observed in the vaccination only group. These data support the notion that, provided high neutralization capacity is elicited by vaccination/boosting approaches, reasonable effectiveness against Omicron may be maintained

A multi-modal dance corpus for research into interaction between humans in virtual environments

We present a new, freely available, multimodal corpus for research into, amongst other areas, real-time realistic interaction between humans in online virtual environments. The specific corpus scenario focuses on an online dance class application scenario where students, with avatars driven by whatever 3D capture technology is locally available to them, can learn choreographies with teacher guidance in an online virtual dance studio. As the dance corpus is focused on this scenario, it consists of student/teacher dance choreographies concurrently captured at two different sites using a variety of media modalities, including synchronised audio rigs, multiple cameras, wearable inertial measurement devices and depth sensors. In the corpus, each of the several dancers performs a number of fixed choreographies, which are graded according to a number of specific evaluation criteria. In addition, ground-truth dance choreography annotations are provided. Furthermore, for unsynchronised sensor modalities, the corpus also includes distinctive events for data stream synchronisation. The total duration of the recorded content is 1 h and 40 min for each single sensor, amounting to 55 h of recordings across all sensors. Although the dance corpus is tailored specifically for an online dance class application scenario, the data is free to download and use for any research and development purposes

Exploring the Contextual Sensitivity of Factors that Determine Cell-to-Cell Variability in Receptor-Mediated Apoptosis

Stochastic fluctuations in gene expression give rise to cell-to-cell variability in protein levels which can potentially cause variability in cellular phenotype. For TRAIL (TNF-related apoptosis-inducing ligand) variability manifests itself as dramatic differences in the time between ligand exposure and the sudden activation of the effector caspases that kill cells. However, the contribution of individual proteins to phenotypic variability has not been explored in detail. In this paper we use feature-based sensitivity analysis as a means to estimate the impact of variation in key apoptosis regulators on variability in the dynamics of cell death. We use Monte Carlo sampling from measured protein concentration distributions in combination with a previously validated ordinary differential equation model of apoptosis to simulate the dynamics of receptor-mediated apoptosis. We find that variation in the concentrations of some proteins matters much more than variation in others and that precisely which proteins matter depends both on the concentrations of other proteins and on whether correlations in protein levels are taken into account. A prediction from simulation that we confirm experimentally is that variability in fate is sensitive to even small increases in the levels of Bcl-2. We also show that sensitivity to Bcl-2 levels is itself sensitive to the levels of interacting proteins. The contextual dependency is implicit in the mathematical formulation of sensitivity, but our data show that it is also important for biologically relevant parameter values. Our work provides a conceptual and practical means to study and understand the impact of cell-to-cell variability in protein expression levels on cell fate using deterministic models and sampling from parameter distributions

Unproductive splicing of SR genes associated with highly conserved and ultraconserved DNA elements

Eukaryotic cells rely on a surveillance mechanism known as the spindle checkpoint to ensure accurate chromosome segregation. The spindle checkpoint prevents sister chromatids from separating until all kinetochores achieve bipolar attachments to the mitotic spindle. Checkpoint proteins tightly inhibit the anaphase-promoting complex (APC), a ubiquitin ligase required for chromosome segregation and progression to anaphase. Unattached kinetochores promote the binding of checkpoint proteins Mad2 and BubR1 to the APC-activator Cdc20, rendering it unable to activate APC. Once all kinetochores are properly attached, however, cells inactivate the checkpoint within minutes, allowing for the rapid and synchronous segregation of chromosomes. How cells switch from strong APC inhibition before kinetochore attachment to rapid APC activation once attachment is complete remains a mystery. Here we show that checkpoint inactivation is an energy-consuming process involving APC-dependent multi-ubiquitination. Multi-ubiquitination by APC leads to the dissociation of Mad2 and BubR1 from Cdc20, a process that is reversed by a Cdc20-directed de-ubiquitinating enzyme. The mutual regulation between checkpoint proteins and APC leaves the cell poised for rapid checkpoint inactivation and ensures that chromosome segregation promptly follows the completion of kinetochore attachment. In addition, our results suggest a mechanistic basis for how cancer cells can have a compromised spindle checkpoint without corresponding mutations in checkpoint genes

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Adhesion and proliferation of living cell on surface functionalized with glycine nanostructures

This research presents the application of glycine amino acid for establishing firm cell-substrate interaction instead of expensive adhesion proteins, peptides and peptide derivatives. The glycine amino acid is chemically functionalized on the coverslip to achieve self-assembled nanostructure. Glycine self-assembly on NaCl treated coverslips is initiated with SiONa+:COO− linkage while their nanostructure is achieved with formation of glycine chain through NH3+:COO− covalent linkage between the adjacent molecules. The functionalization steps are confirmed by Fourier-transform infrared spectroscopy (FTIR) investigation. The atomic force microscopy (AFM) and scanning electron microscopy (SEM) investigations reveal that glycine growth initiates at 4 Hours (H) post-treatment while maximum growth appears after 8H-10H. Both the vertical and horizontal growth of nanostructures show dependence on functionalization periods. Various levels of glycine functionalized surface show different levels of baby hamster kidney (BHK-21) cell adhesion and proliferation efficiency with maximum performance for 10H functionalized surface. The adhesion and proliferation performance of 10H glycine functionalized surface shows negligible difference when compared with glycine-aspartic acid (RGD) functionalized surface. Finally, growth curves obtained from both glycine and RGD functionalized surface reveal exponential growth phage up to 48H followed by stationary phage between 48H and 72H while death of many cells appears from 72H to 96H. Thus, this research concluded that glycine functionalized surface is equally effective for cell adhesion and proliferation