Critical current density and ac harmonic voltage generation in YBa2Cu3O7−δYBa_2Cu_3O_{7-\delta} thin films by the screening technique

The temperature and field dependence of harmonics in voltage $V_n=V'_n-iV"_n$ using the screening technique have been measured for $\mathrm{Y}\mathrm{Ba}_{2}\mathrm{Cu}_3\mathrm{O}_{7-\delta}$ superconducting thin films. Using the Sun model we obtained the curves for the temperature-dependent critical current density $J_c(T)$. In addition, we applied the criterion proposed by Acosta et al. to compute $J_c(T)$. Also, we made used of the empirical law $J_c \propto (1-T/T_c)^n$ as an input in our calculations to reproduce experimental harmonic generation up to the fifth harmonic. We found that most models fit well the fundamental voltage but higher harmonics are poorly reproduced. Such behavior suggests the idea that higher harmonics contain information concerning complex processes like flux creep or thermally assisted flux flow.Comment: 2 pages, 2 figure

A Burst-Based “Hebbian” Learning Rule at Retinogeniculate Synapses Links Retinal Waves to Activity-Dependent Refinement

Patterned spontaneous activity in the developing retina is necessary to drive synaptic refinement in the lateral geniculate nucleus (LGN). Using perforated patch recordings from neurons in LGN slices during the period of eye segregation, we examine how such burst-based activity can instruct this refinement. Retinogeniculate synapses have a novel learning rule that depends on the latencies between pre- and postsynaptic bursts on the order of one second: coincident bursts produce long-lasting synaptic enhancement, whereas non-overlapping bursts produce mild synaptic weakening. It is consistent with “Hebbian” development thought to exist at this synapse, and we demonstrate computationally that such a rule can robustly use retinal waves to drive eye segregation and retinotopic refinement. Thus, by measuring plasticity induced by natural activity patterns, synaptic learning rules can be linked directly to their larger role in instructing the patterning of neural connectivity

Managed Aquifer Recharge as a Tool to Enhance Sustainable Groundwater Management in California

A growing population and an increased demand for water resources have resulted in a global trend of groundwater depletion. Arid and semi-arid climates are particularly susceptible, often relying on groundwater to support large population centers or irrigated agriculture in the absence of sufficient surface water resources. In an effort to increase the security of groundwater resources, managed aquifer recharge (MAR) programs have been developed and implemented globally. MAR is the approach of intentionally harvesting and infiltrating water to recharge depleted aquifer storage. California is a prime example of this growing problem, with three cities that have over a million residents and an agricultural industry that was valued at 47 billion dollars in 2015. The present-day groundwater overdraft of over 100 km3 (since 1962) indicates a clear disparity between surface water supply and water demand within the state. In the face of groundwater overdraft and the anticipated effects of climate change, many new MAR projects are being constructed or investigated throughout California, adding to those that have existed for decades. Some common MAR types utilized in California include injection wells, infiltration basins (also known as spreading basins, percolation basins, or recharge basins), and low-impact development. An emerging MAR type that is actively being investigated is the winter flooding of agricultural fields using existing irrigation infrastructure and excess surface water resources, known as agricultural MAR. California therefore provides an excellent case study to look at the historical use and performance of MAR, ongoing and emerging challenges, novel MAR applications, and the potential for expansion of MAR. Effective MAR projects are an essential tool for increasing groundwater security, both in California and on a global scale. This chapter aims to provide an overview of the most common MAR types and applications within the State of California and neighboring semi-arid regions

Identification of Stage-Specific Breast Markers using Quantitative Proteomics

YesMatched healthy and diseased tissues from breast cancer patients were analyzed by quantitative proteomics. By comparing proteomic profiles of fibroadenoma (benign tumors, three patients), DCIS (noninvasive cancer, three patients), and invasive ductal carcinoma (four patients), we identified protein alterations that correlated with breast cancer progression. Three 8-plex iTRAQ experiments generated an average of 826 protein identifications, of which 402 were common. After excluding those originating from blood, 59 proteins were significantly changed in tumor compared with normal tissues, with the majority associated with invasive carcinomas. Bioinformatics analysis identified relationships between proteins in this subset including roles in redox regulation, lipid transport, protein folding, and proteasomal degradation, with a substantial number increased in expression due to Myc oncogene activation. Three target proteins, cofilin-1 and p23 (increased in invasive carcinoma) and membrane copper amine oxidase 3 (decreased in invasive carcinoma), were subjected to further validation. All three were observed in phenotype-specific breast cancer cell lines, normal (nontransformed) breast cell lines, and primary breast epithelial cells by Western blotting, but only cofilin-1 and p23 were detected by multiple reaction monitoring mass spectrometry analysis. All three proteins were detected by both analytical approaches in matched tissue biopsies emulating the response observed with proteomics analysis. Tissue microarray analysis (361 patients) indicated cofilin-1 staining positively correlating with tumor grade and p23 staining with ER positive status; both therefore merit further investigation as potential biomarkers.Cyprus Research Promotion Foundation, Yorkshire Cancer Researc

Neurons are MHC Class I-Dependent Targets for CD8 T Cells upon Neurotropic Viral Infection

Following infection of the central nervous system (CNS), the immune system is faced with the challenge of eliminating the pathogen without causing significant damage to neurons, which have limited capacities of renewal. In particular, it was thought that neurons were protected from direct attack by cytotoxic T lymphocytes (CTL) because they do not express major histocompatibility class I (MHC I) molecules, at least at steady state. To date, most of our current knowledge on the specifics of neuron-CTL interaction is based on studies artificially inducing MHC I expression on neurons, loading them with exogenous peptide and applying CTL clones or lines often differentiated in culture. Thus, much remains to be uncovered regarding the modalities of the interaction between infected neurons and antiviral CD8 T cells in the course of a natural disease. Here, we used the model of neuroinflammation caused by neurotropic Borna disease virus (BDV), in which virus-specific CTL have been demonstrated as the main immune effectors triggering disease. We tested the pathogenic properties of brain-isolated CD8 T cells against pure neuronal cultures infected with BDV. We observed that BDV infection of cortical neurons triggered a significant up regulation of MHC I molecules, rendering them susceptible to recognition by antiviral CTL, freshly isolated from the brains of acutely infected rats. Using real-time imaging, we analyzed the spatio-temporal relationships between neurons and CTL. Brain-isolated CTL exhibited a reduced mobility and established stable contacts with BDV-infected neurons, in an antigen- and MHC-dependent manner. This interaction induced rapid morphological changes of the neurons, without immediate killing or impairment of electrical activity. Early signs of neuronal apoptosis were detected only hours after this initial contact. Thus, our results show that infected neurons can be recognized efficiently by brain-isolated antiviral CD8 T cells and uncover the unusual modalities of CTL-induced neuronal damage

Invasive Prenatal Diagnostic Testing Recommendations are Influenced by Maternal Age, Statistical Misconception and Perceived Liability

Funding policy and medico-legal climate are part of physicians’ reality and might permeate clinical decisions. This study evaluates the influence of maternal age and government funding on obstetrician/gynecologist recommendation for invasive prenatal testing (i.e. amniocentesis) for Down syndrome (DS), and its association with the physician’s assessment of the risk of liability for medical malpractice unless they recommend amniocentesis. Israeli physicians (N = 171) completed a questionnaire and provided amniocentesis recommendations for women at 18 weeks gestation with normal preliminary screening results, identical except aged 28 and 37. Amniocentesis recommendations were reversed for the younger (‘yes’ regardless of testing results: 6.4%; ‘no’ regardless of testing results: 31.6%) versus older woman (‘yes’ regardless of testing results: 40.9%; ‘no’ regardless of testing results: 7.0%; χ2 = 71.55, p < .01). About half of the physicians endorsed different recommendations per scenario; of these, 65.6% recommended amniocentesis regardless of testing results for the 37-year-old woman. Physicians routinely performing amniocentesis and those advocating for amniocentesis for all women ≥ age 35 were approximately twice as likely to vary their recommendations per scenario. Physicians who perceived risk of liability for malpractice as large were nearly one-and-a-half times more likely to vary recommendations. The results indicate physicians’ recommendations are influenced by maternal age, though age is already incorporated in prenatal DS risk evaluations. The physician’s assessment of the risk that they will be sued unless they recommend amniocentesis may contribute to this spurious influence