Treatment of estrogen-induced dermatitis with omalizumab

In 1945, Drs Bernhard Zondek and Yehuda Bromberg demonstrated intradermal treatment with estrone and estradiol benzoate induced urticarial lesions in some patients.1 Fifty years later, Shelley et al,2 who introduced the concept of progesterone dermatitis several decades prior, defined estrogen dermatitis based on studies of 7 women with premenstrual flares of skin eruptions including papulovesicular, urticarial, or eczematous lesions or generalized pruritus. Previously described therapies for estrogen dermatitis include estrogen desensitization, tamoxifen, leuprolide, and oophorectomy.3 Here we report a case of estrogen-induced dermatitis successfully treated with omalizumab

Effects of Fiber Alignment and Coculture with Endothelial Cells on Osteogenic Differentiation of Mesenchymal Stromal Cells

Impact statement This work demonstrates an effective method of enhancing osteogenesis of mesenchymal stromal cells on electrospun scaffolds through coculturing with endothelial cells. Furthermore, we provide the optimized conditions for cocultures on electrospun fibrous scaffolds and engineered bone tissues with oriented topography on aligned fibers. This study demonstrates promising findings for growing oriented tissue-engineered cocultures with significant increase in osteogenesis over monoculture conditions.Vascularization is a critical process during bone regeneration. The lack of vascular networks leads to insufficient oxygen and nutrients supply, which compromises the survival of regenerated bone. One strategy for improving the survival and osteogenesis of tissue-engineered bone grafts involves the coculture of endothelial cells (ECs) with mesenchymal stromal cells (MSCs). Moreover, bone regeneration is especially challenging due to its unique structural properties with aligned topographical cues, with which stem cells can interact. Inspired by the aligned fibrillar nanostructures in human cancellous bone, we fabricated polycaprolactone (PCL) electrospun fibers with aligned and random morphology, cocultured human MSCs with human umbilical vein ECs (HUVECs), and finally investigated how these two factors modulate osteogenic differentiation of human MSCs (hMSCs). After optimizing cell ratio, a hMSCs/HUVECs ratio (90:10) was considered to be the best combination for osteogenic differentiation. Coculture results showed that hMSCs and HUVECs adhered to and proliferated well on both scaffolds. The aligned structure of PCL fibers strongly influenced the morphology and orientation of hMSCs and HUVECs; however, fiber alignment was observed to not affect alkaline phosphate (ALP) activity or mineralization of hMSCs compared with random scaffolds. More importantly, cocultured cells on both random and aligned scaffolds had significantly higher ALP activities than monoculture groups, which indicated that coculture with HUVECs provided a larger relative contribution to the osteogenesis of hMSCs compared with fiber alignment. Taken together, we conclude that coculture of hMSCs with ECs is an effective strategy to promote osteogenesis on electrospun scaffolds, and aligned fibers could be introduced to regenerate bone tissues with oriented topography without significant deleterious effects on hMSCs differentiation. This study shows the ability to grow oriented tissue-engineered cocultures with significant increases in osteogenesis over monoculture conditions.</p

Adjustable microchip ring trap for cold atoms and molecules

We describe the design and function of a circular magnetic waveguide produced from wires on a microchip for atom interferometry using deBroglie waves. The guide is a two-dimensional magnetic minimum for trapping weak-field seeking states of atoms or molecules with a magnetic dipole moment. The design consists of seven circular wires sharing a common radius. We describe the design, the time-dependent currents of the wires and show that it is possible to form a circular waveguide with adjustable height and gradient while minimizing perturbation resulting from leads or wire crossings. This maximal area geometry is suited for rotation sensing with atom interferometry via the Sagnac effect using either cold atoms, molecules and Bose-condensed systems

Repeatability and reliability of exploratory behavior in proactive and reactive zebrafsh, Danio rerio

Behavioral responses to novel situations often vary and can belong to a suite of correlated behaviors. Characteristic behaviors of different personality types (e.g. stress coping styles) are generally consistent across contexts and time. Here, we compare the repeatability and reliability of exploratory behaviors between zebrafsh strains selectively bred to display contrasting behavioral responses to stressors that represent the proactive-reactive axis. Specifically, we measure exploratory behavior of individual fish in an open field test over five weeks. We quantified the stationary time, average swimming speed and time spent by a fish in the center area. We found a number of strain differences for each behavioral measure. Stationary time was the most repeatable and reliable measure for assessing proactive-reactive behavioral differences. Reactive zebrafish generally showed the highest reliability and repeatability of exploratory behavior compared to proactive zebrafish and a separate wild caught strain. Given the increased interest in the evolutionary consequences and proximate mechanisms of consistent individual differences, it will be important to continue to investigate how different selective pressures may influence expression of stress coping styles and their effects on the consistency of an animal’s behavior

Learning differential equation models from stochastic agent-based model simulations

Agent-based models provide a flexible framework that is frequently used for modelling many biological systems, including cell migration, molecular dynamics, ecology, and epidemiology. Analysis of the model dynamics can be challenging due to their inherent stochasticity and heavy computational requirements. Common approaches to the analysis of agent-based models include extensive Monte Carlo simulation of the model or the derivation of coarse-grained differential equation models to predict the expected or averaged output from the agent-based model. Both of these approaches have limitations, however, as extensive computation of complex agent-based models may be infeasible, and coarse-grained differential equation models can fail to accurately describe model dynamics in certain parameter regimes. We propose that methods from the equation learning field provide a promising, novel, and unifying approach for agent-based model analysis. Equation learning is a recent field of research from data science that aims to infer differential equation models directly from data. We use this tutorial to review how methods from equation learning can be used to learn differential equation models from agent-based model simulations. We demonstrate that this framework is easy to use, requires few model simulations, and accurately predicts model dynamics in parameter regions where coarse-grained differential equation models fail to do so. We highlight these advantages through several case studies involving two agent-based models that are broadly applicable to biological phenomena: a birth-death-migration model commonly used to explore cell biology experiments and a susceptible-infected-recovered model of infectious disease spread

Bioprinting:From Tissue and Organ Development to <i>in Vitro</i> Models

Bioprinting techniques have been flourishing in the field of biofabrication with pronounced and exponential developments in the past years. Novel biomaterial inks used for the formation of bioinks have been developed, allowing the manufacturing of in vitro models and implants tested preclinically with a certain degree of success. Furthermore, incredible advances in cell biology, namely, in pluripotent stem cells, have also contributed to the latest milestones where more relevant tissues or organ-like constructs with a certain degree of functionality can already be obtained. These incredible strides have been possible with a multitude of multidisciplinary teams around the world, working to make bioprinted tissues and organs more relevant and functional. Yet, there is still a long way to go until these biofabricated constructs will be able to reach the clinics. In this review, we summarize the main bioprinting activities linking them to tissue and organ development and physiology. Most bioprinting approaches focus on mimicking fully matured tissues. Future bioprinting strategies might pursue earlier developmental stages of tissues and organs. The continuous convergence of the experts in the fields of material sciences, cell biology, engineering, and many other disciplines will gradually allow us to overcome the barriers identified on the demanding path toward manufacturing and adoption of tissue and organ replacements.</p

Atom chips on direct bonded copper substrates

We present the use of direct bonded copper (DBC) for the straightforward fabrication of high power atom chips. Atom chips using DBC have several benefits: excellent copper/substrate adhesion, high purity, thick (> 100 microns) copper layers, high substrate thermal conductivity, high aspect ratio wires, the potential for rapid (< 8 hr) fabrication, and three dimensional atom chip structures. Two mask options for DBC atom chip fabrication are presented, as well as two methods for etching wire patterns into the copper layer. The wire aspect ratio that optimizes the magnetic field gradient as a function of power dissipation is determined to be 0.84:1 (height:width). The optimal wire thickness as a function of magnetic trapping height is also determined. A test chip, able to support 100 A of current for 2 s without failing, is used to determine the thermal impedance of the DBC. An assembly using two DBC atom chips to provide magnetic confinement is also shown.Comment: 8 pages, 5 figure

Late diagnosis of abdominal aortic aneurysms substantiates underutilization of abdominal aortic aneurysm screening for Medicare beneficiaries

ObjectiveAbdominal aortic aneurysm (AAA) screening remains largely underutilized in the U.S., and it is likely that the proportion of patients with aneurysms requiring prompt treatment is much higher compared with well-screened populations. The goals of this study were to determine the proportion of AAAs that required prompt repair after diagnostic abdominal imaging for U.S. Medicare beneficiaries and to identify patient and hospital factors contributing to early vs late diagnosis of AAA.MethodsData were extracted from Medicare claims records for patients at least 65 years old with complete coverage for 2 years who underwent intact AAA repair from 2006 to 2009. Preoperative ultrasound and computed tomography was tabulated from 2002 to repair. We defined early diagnosis of AAA as a patient with a time interval of greater than 6 months between the first imaging examination and the index procedure, and late diagnosis as patients who underwent the index procedure within 6 months of the first imaging examination.ResultsOf 17,626 patients who underwent AAA repair, 14,948 met inclusion criteria. Mean age was 77.5 ± 6.1 years. Early diagnosis was identified for 60.6% of patients receiving AAA repair, whereas 39.4% were repaired after a late diagnosis. Early diagnosis rates increased from 2006 to 2009 (59.8% to 63.4%; P < .0001) and were more common for intact repair compared with repair after rupture (62.9% vs 35.1%; P < .0001) and for women compared with men (66.3% vs 59.0%; P < .0001). On multivariate analysis, repair of intact vs ruptured AAAs (odds ratio, 3.1; 95% confidence interval, 2.7-3.6) and female sex (odds ratio, 1.4; 95% confidence interval, 1.3-1.5) remained the strongest predictors of surveillance. Although intact repairs were more likely to be diagnosed early, over one-third of patients undergoing repair for ruptured AAAs received diagnostic abdominal imaging greater than 6 months prior to surgery.ConclusionsDespite advances in screening practices, significant missed opportunities remain in the U.S. Medicare population for improving AAA care. It remains common for AAAs to be diagnosed when they are already at risk for rupture. In addition, a significant proportion of patients with early imaging rupture prior to repair. Our findings suggest that improved mechanisms for observational management are needed to ensure optimal preoperative care for patients with AAAs

Biologically-informed neural networks guide mechanistic modeling from sparse experimental data

Biologically-informed neural networks (BINNs), an extension of physics-informed neural networks [1], are introduced and used to discover the underlying dynamics of biological systems from sparse experimental data. In the present work, BINNs are trained in a supervised learning framework to approximate in vitro cell biology assay experiments while respecting a generalized form of the governing reaction-diffusion partial differential equation (PDE). By allowing the diffusion and reaction terms to be multilayer perceptrons (MLPs), the nonlinear forms of these terms can be learned while simultaneously converging to the solution of the governing PDE. Further, the trained MLPs are used to guide the selection of biologically interpretable mechanistic forms of the PDE terms which provides new insights into the biological and physical mechanisms that govern the dynamics of the observed system. The method is evaluated on sparse real-world data from wound healing assays with varying initial cell densities [2]