Increased MRI-based Brain Age in chronic migraine patients

Introduction: Neuroimaging has revealed that migraine is linked to alterations in both the structure and function of the brain. However, the relationship of these changes with aging has not been studied in detail. Here we employ the Brain Age framework to analyze migraine, by building a machine-learning model that predicts age from neuroimaging data. We hypothesize that migraine patients will exhibit an increased Brain Age Gap (the difference between the predicted age and the chronological age) compared to healthy participants. Methods: We trained a machine learning model to predict Brain Age from 2,771 T1-weighted magnetic resonance imaging scans of healthy subjects. The processing pipeline included the automatic segmentation of the images, the extraction of 1,479 imaging features (both morphological and intensity-based), harmonization, feature selection and training inside a 10-fold cross-validation scheme. Separate models based only on morphological and intensity features were also trained, and all the Brain Age models were later applied to a discovery cohort composed of 247 subjects, divided into healthy controls (HC, n=82), episodic migraine (EM, n=91), and chronic migraine patients (CM, n=74). Results: CM patients showed an increased Brain Age Gap compared to HC (4.16 vs -0.56 years, P=0.01). A smaller Brain Age Gap was found for EM patients, not reaching statistical significance (1.21 vs -0.56 years, P=0.19). No associations were found between the Brain Age Gap and headache or migraine frequency, or duration of the disease. Brain imaging features that have previously been associated with migraine were among the main drivers of the differences in the predicted age. Also, the separate analysis using only morphological or intensity-based features revealed different patterns in the Brain Age biomarker in patients with migraine. Conclusion: The brain-predicted age has shown to be a sensitive biomarker of CM patients and can help reveal distinct aging patterns in migraine

Viability of AMURA biomarkers from single-shell diffusion MRI in clinical studies

Diffusion Tensor Imaging (DTI) is the most employed method to assess white matter properties using quantitative parameters derived from diffusion MRI, but it presents known limitations that restrict the evaluation of complex structures. The objective of this study was to validate the reliability and robustness of complementary diffusion measures extracted with a novel approach, Apparent Measures Using Reduced Acquisitions (AMURA), with a typical diffusion MRI acquisition from a clinical context in comparison with DTI with application to clinical studies. Fifty healthy controls, 51 episodic migraine and 56 chronic migraine patients underwent single-shell diffusion MRI. Four DTI-based and eight AMURA-based parameters were compared between groups with tract-based spatial statistics to establish reference results. On the other hand, following a region-based analysis, the measures were assessed for multiple subsamples with diverse reduced sample sizes and their stability was evaluated with the coefficient of quartile variation. To assess the discrimination power of the diffusion measures, we repeated the statistical comparisons with a region-based analysis employing reduced sample sizes with diverse subsets, decreasing 10 subjects per group for consecutive reductions, and using 5,001 different random subsamples. For each sample size, the stability of the diffusion descriptors was evaluated with the coefficient of quartile variation. AMURA measures showed a greater number of statistically significant differences in the reference comparisons between episodic migraine patients and controls compared to DTI. In contrast, a higher number of differences was found with DTI parameters compared to AMURA in the comparisons between both migraine groups. Regarding the assessments reducing the sample size, the AMURA parameters showed a more stable behavior than DTI, showing a lower decrease for each reduced sample size or a higher number of regions with significant differences. However, most AMURA parameters showed lower stability in relation to higher coefficient of quartile variation values than the DTI descriptors, although two AMURA measures showed similar values to DTI. For the synthetic signals, there were AMURA measures with similar quantification to DTI, while other showed similar behavior. These findings suggest that AMURA presents favorable characteristics to identify differences of specific microstructural properties between clinical groups in regions with complex fiber architecture and lower dependency on the sample size or assessing technique than DTI

Structural Discrimination of Robustness in Transcriptional Feedforward Loops for Pattern Formation

Signaling pathways are interconnected to regulatory circuits for sensing the environment and expressing the appropriate genetic profile. In particular, gradients of diffusing molecules (morphogens) determine cell fate at a given position, dictating development and spatial organization. The feedforward loop (FFL) circuit is among the simplest genetic architectures able to generate one-stripe patterns by operating as an amplitude detection device, where high output levels are achieved at intermediate input ones. Here, using a heuristic optimization-based approach, we dissected the design space containing all possible topologies and parameter values of the FFL circuits. We explored the ability of being sensitive or adaptive to variations in the critical morphogen level where cell fate is switched. We found four different solutions for precision, corresponding to the four incoherent architectures, but remarkably only one mode for adaptiveness, the incoherent type 4 (I4-FFL). We further carried out a theoretical study to unveil the design principle for such structural discrimination, finding that the synergistic action and cooperative binding on the downstream promoter are instrumental to achieve absolute adaptive responses. Subsequently, we analyzed the robustness of these optimal circuits against perturbations in the kinetic parameters and molecular noise, which has allowed us to depict a scenario where adaptiveness, parameter sensitivity and noise tolerance are different, correlated facets of the robustness of the I4-FFL circuit. Strikingly, we showed a strong correlation between the input (environment-related) and the intrinsic (mutation-related) susceptibilities. Finally, we discussed the evolution of incoherent regulations in terms of multifunctionality and robustness

図書館組織図

The Microbiotheriid Dromiciops gliroides, also known as 'Monito del Monte', is considered to be a threatened species and the only living representative of this group of South American marsupials. During the last few years, several blood samples from specimens of 'Monito del Monte' captured at Chiloé island in Chile have been investigated for blood parasites. Inspection of blood smears detected a Hepatozoon species infecting red blood cells. The sequences of DNA fragments corresponding to small subunit ribosomal RNA gene revealed two parasitic lineages belonging to Hepatozoon genus. These parasite lineages showed a basal position with respect to Hepatozoon species infecting rodents, reptiles, and amphibians but are phylogenetically distinct from Hepatozoon species infecting the order Carnivora. In addition, the Hepatozoon lineages infecting D. gliroides are also different from those infecting other micro-mammals living in sympatry, as well as from some that have been described to infec

The Spanish Infrared Camera onboard the EUSO-BALLOON (CNES) flight on August 24, 2014

The EUSO-Balloon (CNES) campaign was held during Summer 2014 with a launch on August 24. In the gondola, next to the Photo Detector Module (PDM), a completely isolated Infrared camera was allocated. Also, a helicopter which shooted flashers flew below the balloon. We have retrieved the Cloud Top Height (CTH) with the IR camera, and also the optical depth of the nonclear atmosphere have been inferred with two approaches: The first one is with the comparison of the brightness temperature of the cloud and the real temperature obtained after the pertinent corrections. The second one is by measuring the detected signal from the helicopter flashers by the IR Camera, considering the energy of the flashers and the location of the helicopter

XIPE: the X-ray Imaging Polarimetry Explorer

X-ray polarimetry, sometimes alone, and sometimes coupled to spectral and temporal variability measurements and to imaging, allows a wealth of physical phenomena in astrophysics to be studied. X-ray polarimetry investigates the acceleration process, for example, including those typical of magnetic reconnection in solar flares, but also emission in the strong magnetic fields of neutron stars and white dwarfs. It detects scattering in asymmetric structures such as accretion disks and columns, and in the so-called molecular torus and ionization cones. In addition, it allows fundamental physics in regimes of gravity and of magnetic field intensity not accessible to experiments on the Earth to be probed. Finally, models that describe fundamental interactions (e.g. quantum gravity and the extension of the Standard Model) can be tested. We describe in this paper the X-ray Imaging Polarimetry Explorer (XIPE), proposed in June 2012 to the first ESA call for a small mission with a launch in 2017 but not selected. XIPE is composed of two out of the three existing JET-X telescopes with two Gas Pixel Detectors (GPD) filled with a He-DME mixture at their focus and two additional GPDs filled with pressurized Ar-DME facing the sun. The Minimum Detectable Polarization is 14 % at 1 mCrab in 10E5 s (2-10 keV) and 0.6 % for an X10 class flare. The Half Energy Width, measured at PANTER X-ray test facility (MPE, Germany) with JET-X optics is 24 arcsec. XIPE takes advantage of a low-earth equatorial orbit with Malindi as down-link station and of a Mission Operation Center (MOC) at INPE (Brazil).Comment: 49 pages, 14 figures, 6 tables. Paper published in Experimental Astronomy http://link.springer.com/journal/1068

Updating the Food-Based Dietary Guidelines for the Spanish Population: The Spanish Society of Community Nutrition (SENC) Proposal

Diet-related risk factors and physical inactivity are among the leading risk factors for disability and are responsible for a large proportion of the burden of chronic non-communicable diseases. Food-based dietary guidelines (FBDGs) are useful tools for nutrition policies and public health strategies to promote healthier eating and physical activity. In this paper, we discuss the process followed in developing the dietary guidelines for the Spanish population by the Spanish Society of Community Nutrition (SENC) and further explain the collaboration with primary healthcare practitioners as presented in the context of the NUTRIMAD 2018 international congress of SENC. From a health in all policies approach, SENC convened a group of experts in nutrition and public health to review the evidence on diet-health, nutrient intake and food consumption in the Spanish population, as well as food preparation, determinants and impact of diet on environmental sustainability. The collaborative group drafted the document and designed the graphic icon, which was then subject to a consultation process, discussion, and qualitative evaluation. Next, a collaborative group was established to plan a dissemination strategy, involving delegates from all the primary healthcare scientific societies in Spain. A product of this collaboration was the release of an attractive, easy-to-understand publication

Measurement of the Strong Coupling Constant from Inclusive Jet Production at the Tevatron pˉp\bar pp Collider

We report a measurement of the strong coupling constant, $\alpha_s(M_Z)$, extracted from inclusive jet production in $p\bar{p}$ collisions at $\sqrt{s}=$1800 GeV. The QCD prediction for the evolution of $\alpha_s$ with jet transverse energy $E_T$ is tested over the range 40<$E_T$<450 GeV using $E_T$ for the renormalization scale. The data show good agreement with QCD in the region below 250 GeV. In the text we discuss the data-theory comparison in the region from 250 to 450 GeV. The value of $\alpha_s$ at the mass of the $Z^0$ boson averaged over the range 40<$E_T$<250 GeV is found to be $\alpha_s(M_{Z})= 0.1178 \pm 0.0001{(\rm stat)}^{+0.0081}_{-0.0095}{\rm (exp. syst)}$. The associated theoretical uncertainties are mainly due to the choice of renormalization scale (^{+6%}_{-4%}) and input parton distribution functions (5%).Comment: 7 pages, 3 figures, using RevTeX. Submitted to Physical Review Letter

The atmospheric science of JEM-EUSO

An Atmospheric Monitoring System (AMS) is critical suite of instruments for JEM-EUSO whose aim is to detect Ultra-High Energy Cosmic Rays (UHECR) and (EHECR) from Space. The AMS comprises an advanced space qualified infrared camera and a LIDAR with cross checks provided by a ground-based and airborne Global Light System Stations. Moreover the Slow Data Mode of JEM-EUSO has been proven crucial for the UV background analysis by comparing the UV and IR images. It will also contribute to the investigation of atmospheric effects seen in the data from the GLS or even to our understanding of Space Weather

Modelling the spatial risk of malaria through probability distribution of Anopheles maculipennis s.l. and imported cases

Malaria remains one of the most important infectious diseases globally due to its high incidence and mortality rates. The influx of infected cases from endemic to non-endemic malaria regions like Europe has resulted in a public health concern over sporadic local outbreaks. This is facilitated by the continued presence of competent Anopheles vectors in non-endemic countries. We modelled the potential distribution of the main malaria vector across Spain using the ensemble of eight modelling techniques based on environmental parameters and the Anopheles maculipennis s.l. presence/absence data collected from 2000 to 2020. We then combined this map with the number of imported malaria cases in each municipality to detect the geographic hot spots with a higher risk of local malaria transmission. The malaria vector occurred preferentially in irrigated lands characterized by warm climate conditions and moderate annual precipitation. Some areas surrounding irrigated lands in northern Spain (e.g. Zaragoza, Logroño), mainland areas (e.g. Madrid, Toledo) and in the South (e.g. Huelva), presented a significant likelihood of A. maculipennis s.l. occurrence, with a large overlap with the presence of imported cases of malaria. While the risk of malaria re-emergence in Spain is low, it is not evenly distributed throughout the country. The four recorded local cases of mosquito-borne transmission occurred in areas with a high overlap of imported cases and mosquito presence. Integrating mosquito distribution with human incidence cases provides an effective tool for the quantification of large-scale geographic variation in transmission risk and pinpointing priority areas for targeted surveillance and prevention