Gepants, calcitonin gene-related peptide antagonists, for abortive treatment of migraine: current status

Migraine is a neurovascular disorder characterized by unilateral, recurrent, pulsating, throbbing, and moderate to severe headache. Triptans use is often limited by their poor efficacy, reports of poor responders, and contraindicated in patients with cardiovascular disorders. Calcitonin gene-related peptide (CGRP), a neuropeptide, regulates vascular tonicity as well as potent pain mediator, and both the mechanisms involved in development of migraine headache. Gepants are non-peptide, small molecules, highly selective, and potent CGRP antagonists. These novel drugs have been approved for abortive treatment of acute migraine with or without aura. These are being evaluated for their effectiveness and showing promising results in the prevention of migraine. Gepants do not have vasoconstrictive properties, are safe to use in patients with cardiovascular risk, and best alternative to triptan therapy. These are available in tablet, orally disintegrating tablet, and nasal forms to improve patient compliance. Ubrogepant and rimegepant are the two oral CGRP antagonists approved whereas atogepant and zavegepant are at late stage of development for approval

Comparison of Artificial Intelligence based approaches to cell function prediction

Predicting Retinal Pigment Epithelium (RPE) cell functions in stem cell implants using non-invasive bright field microscopy imaging is a critical task for clinical deployment of stem cell therapies. Such cell function predictions can be carried out using Artificial Intelligence (AI) based models. In this paper we used Traditional Machine Learning (TML) and Deep Learning (DL) based AI models for cell function prediction tasks. TML models depend on feature engineering and DL models perform feature engineering automatically but have higher modeling complexity. This work aims at exploring the tradeoffs between three approaches using TML and DL based models for RPE cell function prediction from microscopy images and at understanding the accuracy relationship between pixel-, cell feature-, and implant label-level accuracies of models. Among the three compared approaches to cell function prediction, the direct approach to cell function prediction from images is slightly more accurate in comparison to indirect approaches using intermediate segmentation and/or feature engineering steps. We also evaluated accuracy variations with respect to model selections (five TML models and two DL models) and model configurations (with and without transfer learning). Finally, we quantified the relationships between segmentation accuracy and the number of samples used for training a model, segmentation accuracy and cell feature error, and cell feature error and accuracy of implant labels. We concluded that for the RPE cell data set, there is a monotonic relationship between the number of training samples and image segmentation accuracy, and between segmentation accuracy and cell feature error, but there is no such a relationship between segmentation accuracy and accuracy of RPE implant labels

Non-Supersymmetric Attractor Flow in Symmetric Spaces

We derive extremal black hole solutions for a variety of four dimensional models which, after Kaluza-Klein reduction, admit a description in terms of 3D gravity coupled to a sigma model with symmetric target space. The solutions are in correspondence with certain nilpotent generators of the isometry group. In particular, we provide the exact solution for a non-BPS black hole with generic charges and asymptotic moduli in N=2 supergravity coupled to one vector multiplet. Multi-centered solutions can also be generated with this technique. It is shown that the non-supersymmetric solutions lack the intricate moduli space of bound configurations that are typical of the supersymmetric case.Comment: 50 pages, 4 figures; v2: Reference added. To appear in JHE

Deep learning predicts function of live retinal pigment epithelium from quantitative microscopy.

Increases in the number of cell therapies in the preclinical and clinical phases have prompted the need for reliable and non-invasive assays to validate transplant function in clinical biomanufacturing. We developed a robust characterization methodology composed of quantitative bright-field absorbance microscopy (QBAM) and deep neural networks (DNNs) to non-invasively predict tissue function and cellular donor identity. The methodology was validated using clinical-grade induced pluripotent stem cell derived retinal pigment epithelial cells (iPSC-RPE). QBAM images of iPSC-RPE were used to train DNNs that predicted iPSC-RPE monolayer transepithelial resistance, predicted polarized vascular endothelial growth factor (VEGF) secretion, and matched iPSC-RPE monolayers to the stem cell donors. DNN predictions were supplemented with traditional machine learning algorithms that identified shape and texture features of single cells that were used to predict tissue function and iPSC donor identity. These results demonstrate non-invasive cell therapy characterization can be achieved with QBAM and machine learning

Eternal Chaotic Inflation is Prohibited by Weak Gravity Conjecture

We investigate whether the eternal chaotic inflation can be achieved when the weak gravity conjecture is taken into account. We show that even the assisted chaotic inflation with potential $\lambda\phi^4$ or $m^2\phi^2$ can not be eternal. The effective field theory description for the inflaton field breaks down before inflation reaches the eternal regime. We also find that the total number of e-folds is still bounded by the inflationary entropy for the assisted inflation.Comment: 10 page

An integrated genetic map and a new set of simple sequence repeat markers for pearl millet, Pennisetum glaucum

Over the past 10 years, resources have been established for the genetic analysis of pearl millet, Pennisetum glaucum (L.) R. Br., an important staple crop of the semi-arid regions of India and Africa. Among these resources are detailed genetic maps containing both homologous and heterologous restriction fragment length polymorphism (RFLP) markers, and simple sequence repeats (SSRs). Genetic maps produced in four different crosses have been integrated to develop a consensus map of 353 RFLP and 65 SSR markers. Some 85% of the markers are clustered and occupy less than a third of the total map length. This phenomenon is independent of the cross. Our data suggest that extreme localization of recombination toward the chromosome ends, resulting in gaps on the genetic map of 30 cM or more in the distal regions, is typical for pearl millet. The unequal distribution of recombination has consequences for the transfer of genes controlling important agronomic traits from donor to elite pearl millet germplasm. The paper also describes the generation of 44 SSR markers from a (CA)n-enriched small-insert genomic library. Previously, pearl millet SSRs had been generated from BAC clones, and the relative merits of both methodologies are discusse

Warped AdS_3 Black Holes

Three dimensional topologically massive gravity (TMG) with a negative cosmological constant -\ell^{-2} and positive Newton constant G admits an AdS_3 vacuum solution for any value of the graviton mass \mu. These are all known to be perturbatively unstable except at the recently explored chiral point \mu\ell=1. However we show herein that for every value of \mu\ell< 3 there are two other (potentially stable) vacuum solutions given by SL(2,R)x U(1)-invariant warped AdS_3 geometries, with a timelike or spacelike U(1) isometry. Critical behavior occurs at \mu\ell=3, where the warping transitions from a stretching to a squashing, and there are a pair of warped solutions with a null U(1) isometry. For \mu\ell>3, there are known warped black hole solutions which are asymptotic to warped AdS_3. We show that these black holes are discrete quotients of warped AdS_3 just as BTZ black holes are discrete quotients of ordinary AdS_3. Moreover new solutions of this type, relevant to any theory with warped AdS_3 solutions, are exhibited. Finally we note that the black hole thermodynamics is consistent with the hypothesis that, for \mu\ell>3, the warped AdS_3 ground state of TMG is holographically dual to a 2D boundary CFT with central charges c_R={15(\mu\ell)^2+81\over G\mu((\mu\ell)^2+27)} and c_L={12 \mu\ell^2\over G((\mu\ell)^2+27)}.Comment: 29 page

Angiotensin-(1–7) and the G Protein-Coupled Receptor Mas Are Key Players in Renal Inflammation

Angiotensin (Ang) II mediates pathophysiologial changes in the kidney. Ang-(1–7) by interacting with the G protein-coupled receptor Mas may also have important biological activities

Effects of ursodeoxycholic acid on the gut microbiome and colorectal adenoma development

It has been previously reported that ursodeoxycholic acid (UDCA), a therapeutic bile acid, reduced risk for advanced colorectal adenoma in men but not women. Interactions between the gut microbiome and fecal bile acid composition as a factor in colorectal cancer neoplasia have been postulated but evidence is limited to small cohorts and animal studies. Using banked stool samples collected as part of a phase III randomized clinical trial of UDCA for the prevention of colorectal adenomatous polyps, we compared change in the microbiome composition after a 3-year intervention in a subset of participants randomized to oral UDCA at 8-10 mg/kg of body weight per day (n = 198) or placebo (n = 203). Study participants randomized to UDCA experienced compositional changes in their microbiome that were statistically more similar to other individuals in the UDCA arm than to those in the placebo arm. This reflected a UDCA-associated shift in microbial community composition (P 0.05). These UDCA-associated shifts in microbial community distance metrics from baseline to end-of-study were not associated with risk of any or advanced adenoma (all P > 0.05) in men or women. Separate analyses of microbial networks revealed an overrepresentation of Faecalibacterium prausnitzii in the post-UDCA arm and an inverse relationship between F prausnitzii and Ruminococcus gnavus. In men who received UDCA, the overrepresentation of F prausnitzii and underrepresentation of R gnavus were more prominent in those with no adenoma recurrence at follow-up compared to men with recurrence. This relationship was not observed in women. Daily UDCA use modestly influences the relative abundance of microbial species in stool and affects the microbial network composition with suggestive evidence for sex-specific effects of UDCA on stool microbial community composition as a modifier of colorectal adenoma risk.Partnership for Native American Cancer Prevention [NIH/NCI U54CA143924, U54CA143925]; NSF [1565100]; Biostatistics and Tissue Acquisition and Cellular/Molecular Analysis Shared Resources - NCI [P30CA023074]; [R01 CA151708]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]