Ultracold fermions in a one-dimensional bipartite optical lattice: metal-insulator transitions driven by shaking

We describe the behavior of a system of fermionic atoms loaded in a bipartite one-dimensional optical lattice that is under the action of an external time-periodic driving force. By using Floquet theory, an effective model with renormalized hopping coefficients is derived. The insulating behavior characterizing the system at half-filling in the absence of driving is dynamically suppressed and for particular values of the driving parameter the system becomes either a standard metal or an unconventional metal with four Fermi points. We use the bosonization technique to investigate the effect of on-site Hubbard interactions on the four Fermi-point metal-insulator phase transition. Attractive interactions are expected to enlarge the regime of parameters where the unconventional metallic phase arises, whereas repulsive interactions reduce it. This metallic phase is known to be a Luther-Emery liquid (spin gapped metal) for both, repulsive and attractive interactions, contrarily to the usual Hubbard model which exhibits a Mott insulator phase for repulsive interactions. Ultracold fermions in driven one-dimensional bipartite optical lattices provide an interesting platform for the realization of this long studied four Fermi-point unconventional metal.Comment: 11 pages, 6 figure

Cortical responses to natural speech reflect probabilistic phonotactics

Humans comprehend speech despite the various challenges of real-world environments, such as loud noise and mispronunciation. Our auditory system is robust to these thanks to the integration of the upcoming sensory input with prior knowledge and expectations built on language-specific regularities. One such regularity regards the permissible phoneme sequences, which determine the likelihood that a word belongs to a given language (phonotactic probability; “blick” is more likely to be an English word than “bnick”). Previous research suggested that violations of these rules modulate brain evoked responses such as the N400 and the late positive complex. Yet several fundamental questions remain unresolved, especially regarding the neural encoding and integration strategy of phonotactic information. Here, we used linear modelling approaches to assess the influence of phonotactic probabilities on the brain responses to narrative speech measured with non-invasive EEG. We found that the relationship between continuous speech and EEG responses is best described when the speech descriptor includes phonotactic probabilities. This provides us with a methodology to isolate and measure the brain responses to phonotactics using natural speech at the individual subject-level. Furthermore, such low-frequency signals showed the strongest speech-EEG interactions at latencies of 100-400 ms, supporting a pre-lexical role of phonotactic information

On the evolution of decoys in plant immune systems

The Guard-Guardee model for plant immunity describes how resistance proteins (guards) in host cells monitor host target proteins (guardees) that are manipulated by pathogen effector proteins. A recently suggested extension of this model includes decoys, which are duplicated copies of guardee proteins, and which have the sole function to attract the effector and, when modified by the effector, trigger the plant immune response. Here we present a proof-of-principle model for the functioning of decoys in plant immunity, quantitatively developing this experimentally-derived concept. Our model links the basic cellular chemistry to the outcomes of pathogen infection and resulting fitness costs for the host. In particular, the model allows identification of conditions under which it is optimal for decoys to act as triggers for the plant immune response, and of conditions under which it is optimal for decoys to act as sinks that bind the pathogen effectors but do not trigger an immune response.Comment: 15 pages, 6 figure

A multiwavelength numerical model in support of quantitative retrievals of aerosol properties from automated lidar ceilometers and test applications for AOT and PM10 estimation

Abstract. The use of automated lidar ceilometer (ALC) systems for the aerosol vertically resolved characterization has increased in recent years thanks to their low construction and operation costs and their capability of providing continuous unattended measurements. At the same time there is a need to convert the ALC signals into usable geophysical quantities. In fact, the quantitative assessment of the aerosol properties from ALC measurements and the relevant assimilation in meteorological forecast models is amongst the main objectives of the EU COST Action TOPROF ("Towards operational ground-based profiling with ALCs, Doppler lidars and microwave radiometers for improving weather forecasts"). Concurrently, the E-PROFILE program of the European Meteorological Services Network (EUMETNET) focuses on the harmonization of ALC measurements and data provision across Europe. Within these frameworks, we implemented a model-assisted methodology to retrieve key aerosol properties (extinction coefficient, surface area, and volume) from elastic lidar and/or ALC measurements. The method is based on results from a large set of aerosol scattering simulations (Mie theory) performed at UV, visible, and near-IR wavelengths using a Monte Carlo approach to select the input aerosol microphysical properties. An average "continental aerosol type" (i.e., clean to moderately polluted continental aerosol conditions) is addressed in this study. Based on the simulation results, we derive mean functional relationships linking the aerosol backscatter coefficients to the abovementioned variables. Applied in the data inversion of single-wavelength lidars and/or ALCs, these relationships allow quantitative determination of the vertically resolved aerosol backscatter, extinction, volume, and surface area and, in turn, of the extinction-to-backscatter ratios (i.e., the lidar ratios, LRs) and extinction-to-volume conversion factor (cv) at 355, 532, and 1064 nm. These variables provide valuable information for visibility, radiative transfer, and air quality applications. This study also includes (1) validation of the model simulations with real measurements and (2) test applications of the proposed model-based ALC inversion methodology. In particular, our model simulations were compared to backscatter and extinction coefficients independently retrieved by Raman lidar systems operating at different continental sites within the European Aerosol Research Lidar Network (EARLINET). This comparison shows good model–measurement agreement, with LR discrepancies below 20 %. The model-assisted quantitative retrieval of both aerosol extinction and volume was then tested using raw data from three different ALCs systems (CHM 15k Nimbus), operating within the Italian Automated LIdar-CEilometer network (ALICEnet). For this purpose, a 1-year record of the ALC-derived aerosol optical thickness (AOT) at each site was compared to direct AOT measurements performed by colocated sun–sky photometers. This comparison shows an overall AOT agreement within 30 % at all sites. At one site, the model-assisted ALC estimation of the aerosol volume and mass (i.e., PM10) in the lowermost levels was compared to values measured at the surface level by colocated in situ instrumentation. Within this exercise, the ALC-derived daily-mean mass concentration was found to reproduce the corresponding (EU regulated) PM10 values measured by the local air quality agency well in terms of both temporal variability and absolute values. Although limited in space and time, the good performances of the proposed approach suggest it could possibly represent a valid option to extend the capabilities of ALCs to provide quantitative information for operational air quality and meteorological monitoring

Molusco contagioso: sorologia e microscopia eletrônica em vinte e um pacientes

Twenty one cases of molluscum contagiosum virus disease were collected for electron microscopical and serological tests. Molluscum virus was detected in the crust, inside the vacuoles formed in the keratinocytes cells. The patients developed specific antibodies to the virus detected by complement fixation test.Vinte e um casos de molusco contagioso foram escolhidos para serem analisados por testes sorológicos e de microscopia eletrônica. O vírus do molusco foi detectado nas crostas e observados também nos vacúolos formados dentro dos queratinócitos. Os pacientes desenvolveram anticorpos fixadores do complemento para o vírus

Cell-Free DNA and CXCL10 Derived from Bronchoalveolar Lavage Predict Lung Transplant Survival.

Standard methods for detecting chronic lung allograft dysfunction (CLAD) and rejection have poor sensitivity and specificity and have conventionally required bronchoscopies and biopsies. Plasma cell-free DNA (cfDNA) has been shown to be increased in various types of allograft injury in transplant recipients and CXCL10 has been reported to be increased in the lung tissue of patients undergoing CLAD. This study used a novel cfDNA and CXCL10 assay to evaluate the noninvasive assessment of CLAD phenotype and prediction of survival from bronchoalveolar lavage (BAL) fluid. A total of 60 BAL samples (20 with bronchiolitis obliterans (BOS), 20 with restrictive allograft syndrome (RAS), and 20 with stable allografts (STA)) were collected from 60 unique lung transplant patients; cfDNA and CXCL10 were measured by the ELISA-based KIT assay. Median cfDNA was significantly higher in BOS patients (6739 genomic equivalents (GE)/mL) versus STA (2920 GE/mL) and RAS (4174 GE/mL) (p < 0.01 all comparisons). Likelihood ratio tests revealed a significant association of overall survival with cfDNA (p = 0.0083), CXCL10 (p = 0.0146), and the interaction of cfDNA and CXCL10 (p = 0.023) based on multivariate Cox proportional hazards regression. Dichotomizing patients based on the median cfDNA level controlled for the mean level of CXCL10 revealed an over two-fold longer median overall survival time in patients with low levels of cfDNA. The KIT assay could predict allograft survival with superior performance compared with traditional biomarkers. These data support the pursuit of larger prospective studies to evaluate the predictive performance of cfDNA and CXCL10 prior to lung allograft failure

IL-17 polarization of MAIT cells is derived from the activation of two different pathways

MAIT cells are expanded in salivary glands of patients with Sjogren's syndrome and are IL-17 polarized. IL-7 and IL-23 induce IL-17 production activating two different pathways: IL-7 stimulation induces in fact a significant STAT3 and HIF1alpha upregulation, conversely, IL-23 stimulation significantly induces RORc overexpression in MAIT cells of patients with Sjogren's syndrome