Many-body Effects in Angle-resolved Photoemission: Quasiparticle Energy and Lifetime of a Mo(110) Surface State

In a high-resolution photoemission study of a Mo(110) surface state various contributions to the measured width and energy of the quasiparticle peak are investigated. Electron-phonon coupling, electron-electron interactions and scattering from defects are all identified mechanisms responsible for the finite lifetime of a valence photo-hole. The electron-phonon induced mass enhancement and rapid change of the photo-hole lifetime near the Fermi level are observed for the first time.Comment: RevTEX, 4 pages, 4 figures, to be published in PR

Charge-imbalance effects in intrinsic Josephson systems

We report on two types of experiments with intrinsic Josephson systems made from layered superconductors which show clear evidence of nonequilibrium effects: 1. In 2-point measurements of IV-curves in the presence of high- frequency radiation a shift of the voltage of Shapiro steps from the canonical value hf/(2e) has been observed. 2. In the IV-curves of double-mesa structures an influence of the current through one mesa on the voltage measured on the other mesa is detected. Both effects can be explained by charge-imbalance on the superconducting layers produced by the quasi-particle current, and can be described successfully by a recently developed theory of nonequilibrium effects in intrinsic Josephson systems.Comment: 8pages, 9figures, submitted to Phys. Rev.

Lymph node-derived donor encephalitogenic CD4+ T cells in C57BL/6 mice adoptive transfer experimental autoimmune encephalomyelitis highly express GM-CSF and T-bet

Experimental autoimmune encephalomyelitis (EAE) is a relevant animal model for the human demyelinating inflammatory disorder of the central nervous system (CNS), multiple sclerosis (MS). Induction of EAE by adoptive transfer allows studying the role of the donor T lymphocyte in disease pathogenesis. It has been challenging to reliably induce adoptive transfer EAE in C57BL/6 (H-2b) mice. The goal of this study was to develop a reproducible and high yield protocol for adoptive transfer EAE in C57BL/6 mice. A step-wise experimental approach permitted us to develop a protocol that resulted in a consistent relatively high disease incidence of ~70% in recipient mice. Donor mice were immunized with myelin oligodendrocyte glycoprotein (MOG)p35-55 in complete Freund's adjuvant (CFA) followed by pertussis toxin (PT). Only lymph node cells (LNC) isolated at day 12 post immunization, and restimulated in vitro for 72 hours with 10 μg/mL of MOGp35-55 and 0.5 ng/mL of interleukin-12 (IL-12) were able to transfer disease. The ability of LNC to transfer disease was associated with the presence of inflammatory infiltrates in the CNS at day 12. Interferon gamma (IFNγ) was produced at comparable levels in cell cultures prepared from mice at both day 6 and day 12 post immunization. By contrast, there was a trend towards a negative association between IL-17 and disease susceptibility in our EAE model. The amount of GM-CSF secreted was significantly increased in the culture supernatants from cells collected at day 12 post immunization versus those collected at day 6 post-immunization. Activated CD4+ T cells present in the day 12 LNC cultures maintained expression of the transcription factor T-bet, which has been shown to regulate the expression of the IL-23 receptor. Also, there was an increased prevalence of MOGp35-55-specific CD4+ T cells in day 12 LNC after in vitro re-stimulation. In summary, encephalitogenic LNC that adoptively transfer EAE in C57BL/6 mice were not characterized by a single biomarker in our study, but by a composite of inflammatory markers. Our data further suggest that GM-CSF expression by CD4+ T cells regulated by IL-23 contributes to their encephalitogenicity in our EAE model

Digital maturity and its determinants in General Practice: a cross- sectional study in 20 countries

Background: The extent to which digital technologies are employed to promote the delivery of high-quality healthcare is known as Digital Maturity. Individual and systemic digital maturity are both necessary to ensure a successful, scalable and sustainable digital transformation in healthcare. However, digital maturity in primary care has been scarcely evaluated. Objectives: This study assessed the digital maturity in General Practice (GP) globally and evaluated its association with participants' demographic characteristics, practice characteristics and features of Electronic Health Records (EHRs) use. Methods: GPs across 20 countries completed an online questionnaire between June and September 2020. Demographic data, practice characteristics, and features of EHRs use were collected. Digital maturity was evaluated through a framework based on usage, resources and abilities (divided in this study in its collective and individual components), interoperability, general evaluation methods and impact of digital technologies. Each dimension was rated as 1 or 0. The digital maturity score was calculated as the sum of the six dimensions and ranged between 0 to 6 (maximum digital maturity). Multivariable linear regression was used to model the total score, while multivariable logistic regression was used to model the probability of meeting each dimension of the score. Results: One thousand six hundred GPs (61% female, 68% Europeans) participated. GPs had a median digital maturity of 4 (P25–P75: 3–5). Positive associations with digital maturity were found with: male gender [B = 0.18 (95% CI 0.01; 0.36)], use of EHRs for longer periods [B = 0.45 (95% CI 0.35; 0.54)] and higher frequencies of access to EHRs [B = 0.33 (95% CI 0.17; 0.48)]. Practicing in a rural setting was negatively associated with digital maturity [B = −0.25 (95%CI −0.43; −0.08)]. Usage (90%) was the most acknowledged dimension while interoperability (47%) and use of best practice general evaluation methods (28%) were the least. Shorter durations of EHRs use were negatively associated with all digital maturity dimensions (aOR from 0.09 to 0.77). Conclusion: Our study demonstrated notable factors that impact digital maturity and exposed discrepancies in digital transformation across healthcare settings. It provides guidance for policymakers to develop more efficacious interventions to hasten the digital transformation of General Practice

Practice setting and secondary prevention of coronary artery disease

Introduction: Patients with established coronary artery disease (CAD) are at high risk of recurrent cardiovascular events. The aim of the analysis was to compare time trends in the extent to which cardiovascular prevention guidelines have been implemented by primary care physicians and specialists. Material and methods: Five hospitals with cardiology departments serving the city and surrounding districts in the southern part of Poland participated in the study. Consecutive patients hospitalized due to an acute coronary syndrome or for a myocardial revascularization procedure were recruited and interviewed 6-18 months after hospitalization. The surveys were carried out in 1997-1998, 1999-2000, 2006-2007 and 2011-2013. Results: The proportion of smokers increased from 16.0% in 1997–1998 to 16.4% in 2011-2013 among those who declared that a cardiologist in a hospital outpatient clinic decided about the treatment, from 17.5% to 34.0% (p < 0.01) among those treated by a primary care physician, and from 7.0% to 19.7% (p = 0.06) among patients treated in private cardiology practices. The corresponding proportions were 44.6% and 42.4% (p < 0.01), 47.7% and 52.8% (p = 0.53), 44.2% and 42.2% (p = 0.75) for high blood pressure, and 42.5% and 71.2% (p < 0.001), 51.4% and 79.6% (p < 0.001), 52.4% and 72.4% (p < 0.01) for LDL cholesterol level not at recommended goal. The proportion of patients prescribed cardioprotective medications increased in every analyzed group. Conclusions: The control of cardiovascular risk in CAD patients has only slightly improved since 1997/98 in all health care settings. The greatest potential for further improvement was found among patients whose post-hospital care is provided by primary care physicians. It is associated with promotion of a no-smoking policy and enhanced prescription of guideline-recommended drugs

Spatial and temporal heterogeneity of mouse and human microglia at single-cell resolution

Microglia have critical roles not only in neural development and homeostasis, but also in neurodegenerative and neuroinflammatory diseases of the central nervous system(1-4). These highly diverse and specialized functions may be executed by subsets of microglia that already exist in situ, or by specific subsets of microglia that develop from a homogeneous pool of cells on demand. However, little is known about the presence of spatially and temporally restricted subclasses of microglia in the central nervous system during development or disease. Here we combine massively parallel single-cell analysis, single-molecule fluorescence in situ hybridization, advanced immunohistochemistry and computational modelling to comprehensively characterize subclasses of microglia in multiple regions of the central nervous system during development and disease. Single-cell analysis of tissues of the central nervous system during homeostasis in mice revealed specific time- and region-dependent subtypes of microglia. Demyelinating and neurodegenerative diseases evoked context-dependent subtypes of microglia with distinct molecular hallmarks and diverse cellular kinetics. Corresponding clusters of microglia were also identified in healthy human brains, and the brains of patients with multiple sclerosis. Our data provide insights into the endogenous immune system of the central nervous system during development, homeostasis and disease, and may also provide new targets for the treatment of neurodegenerative and neuroinflammatory pathologies

PEG Minocycline-Liposomes Ameliorate CNS Autoimmune Disease

Minocycline is an oral tetracycline derivative with good bioavailability in the central nervous system (CNS). Minocycline, a potent inhibitor of matrix metalloproteinase (MMP)-9, attenuates disease activity in experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis (MS). Potential adverse effects associated with long-term daily minocycline therapy in human patients are concerning. Here, we investigated whether less frequent treatment with long-circulating polyethylene glycol (PEG) minocycline liposomes are effective in treating EAE.Performing in vitro time kinetic studies of PEG minocycline-liposomes in human peripheral blood mononuclear cells (PBMCs), we determined that PEG minocycline-liposome preparations stabilized with CaCl(2) are effective in diminishing MMP-9 activity. Intravenous injections of PEG minocycline-liposomes every five days were as effective in ameliorating clinical EAE as daily intraperitoneal injections of minocycline. Treatment of animals with PEG minocycline-liposomes significantly reduced the number of CNS-infiltrating leukocytes, and the overall expression of MMP-9 in the CNS. There was also a significant suppression of MMP-9 expression and proteolytic activity in splenocytes of treated animals, but not in CNS-infiltrating leukocytes. Thus, leukocytes gaining access to the brain and spinal cord require the same absolute amount of MMP-9 in all treatment groups, but minocycline decreases the absolute cell number.Our data indicate that less frequent injections of PEG minocycline-liposomes are an effective alternative pharmacotherapy to daily minocycline injections for the treatment of CNS autoimmune diseases. Also, inhibition of MMP-9 remains a promising treatment target in EAE and patients with MS

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons

An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows (“explaining away”) and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons