Inconsistencies on the Hubble tension from the ages of the oldest astrophysical objects

Recently different cosmological measurements have shown a tension in the value of the Hubble constant, $H_0$. Assuming the $\Lambda$CDM model, the Planck satellite mission has inferred the Hubble constant from the cosmic microwave background (CMB) anisotropies to be $H_0 = 67.4 \pm 0.5 \, \rm{km \, s^{-1} \, Mpc^{-1}}$. On the other hand, low redshift measurements such as those using Cepheid variables and supernovae Type Ia (SNIa) have obtained a significantly larger value. For instance, Riess et al. reported $H_0 = 73.04 \pm 1.04 \, \rm{km \, s^{-1} \, Mpc^{-1}}$, which is $5\sigma$ apart of the prediction from Planck observations. This tension is a major problem in cosmology nowadays, and it is not clear yet if it comes from systematic effects or new physics. The use of new methods to infer the Hubble constant is therefore essential to shed light on this matter. In this paper, we discuss using the age of the oldest astrophysical objects (OAO) to probe the Hubble tension. We show that, although this data can provide additional information, the method can also artificially introduce a tension.Comment: 6 pages, 6 figure

Dermoscopic and Clinical Response Predictor Factors in Nonsegmental Vitiligo Treated with Narrowband Ultraviolet B Phototherapy: A Prospective Observational Study

Introduction: Few data on possible local factors that can influence the achievement of response in nonsegmental vitiligo (NSV) treated with narrowband ultraviolet B (Nb-UVB) phototherapy are available. Our objective is to evaluate possible correlations between therapeutic outcomes and dermoscopic and local (lesional) clinical findings of vitiligous lesions undergoing Nb-UVB phototherapy to find positive and/or negative response predictor factors to such treatment. Methods: For each target patch, we calculated the extension area using a computer-aided method and assessed dermoscopic and local (lesional) clinical findings at baseline. After 30 phototherapy sessions (twice weekly), surface area of the lesions was reevaluated to assess clinical improvement, correlating the therapeutic outcome with initial clinical and dermoscopic features. Results: A total of 70 lesions were finally included in the study. At the end of therapy, 18 patches (25.7%) achieved improvement, and the presence of perifollicular pigmentation on baseline dermoscopic examination was found to be associated with a 12-fold higher probability of having a positive therapeutic outcome. Similarly, face localization was also correlated with clinical amelioration, with a sevenfold higher probability for improvement. No association (p > 0.05) between therapeutic outcomes (either good or poor) and other dermoscopic or local clinical variables (including leukotrichia) was observed. Conclusions: Therapeutic response of vitiligo to Nb-UVB phototherapy may be positively affected by local features of the lesions, i.e., face localization and presence of perifollicular pigmentation on baseline dermoscopic examination, which might be considered as positive response predictor factors to optimize treatment of vitiligo

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR)

<p>Abstract</p> <p>Background</p> <p>Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods.</p> <p>Methods</p> <p>We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected <it>a priori </it>determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision.</p> <p>Application</p> <p>We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population.</p> <p>Conclusion</p> <p>This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy.</p

A Dopaminergic Gene Cluster in the Prefrontal Cortex Predicts Performance Indicative of General Intelligence in Genetically Heterogeneous Mice

Background: Genetically heterogeneous mice express a trait that is qualitatively and psychometrically analogous to general intelligence in humans, and as in humans, this trait co-varies with the processing efficacy of working memory (including its dependence on selective attention). Dopamine signaling in the prefrontal cortex (PFC) has been established to play a critical role in animals ’ performance in both working memory and selective attention tasks. Owing to this role of the PFC in the regulation of working memory, here we compared PFC gene expression profiles of 60 genetically diverse CD-1 mice that exhibited a wide range of general learning abilities (i.e., aggregate performance across five diverse learning tasks). Methodology/Principal Findings: Animals ’ general cognitive abilities were first determined based on their aggregate performance across a battery of five diverse learning tasks. With a procedure designed to minimize false positive identifications, analysis of gene expression microarrays (comprised of &lt;25,000 genes) identified a small number (,20) of genes that were differentially expressed across animals that exhibited fast and slow aggregate learning abilities. Of these genes, one functional cluster was identified, and this cluster (Darpp-32, Drd1a, and Rgs9) is an established modulator of dopamine signaling. Subsequent quantitative PCR found that expression of these dopaminegic genes plus one vascular gene (Nudt6) were significantly correlated with individual animal’s general cognitive performance. Conclusions/Significance: These results indicate that D1-mediated dopamine signaling in the PFC, possibly through it