The Islamic Republic of Iran reported its first COVID-19 cases by 19th February 2020, since then it has become one of the most affected countries, with more than 73,000 cases and 4,585 deaths to this date. Spatial modeling could be used to approach an understanding of structural and sociodemographic factors that have impacted COVID-19 spread at a province-level in Iran. Therefore, in the present paper, we developed a spatial statistical approach to describe how COVID-19 cases are spatially distributed and to identify significant spatial clusters of cases and how socioeconomic and climatic features of Iranian provinces might predict the number of cases. The analyses are applied to cumulative cases of the disease from February 19th to March 18th. They correspond to obtaining maps associated with quartiles for rates of COVID-19 cases smoothed through a Bayesian technique and relative risks, the calculation of global (Moran’s I) and local indicators of spatial autocorrelation (LISA), both univariate and bivariate, to derive significant clustering, and the fit of a multivariate spatial lag model considering a set of variables potentially affecting the presence of the disease. We identified a cluster of provinces with significantly higher rates of COVID-19 cases around Tehran (p-value< 0.05), indicating that the COVID-19 spread within Iran was spatially correlated. Urbanized, highly connected provinces with older population structures and higher average temperatures were the most susceptible to present a higher number of COVID-19 cases (p-value < 0.05). Interestingly, literacy is a factor that is associated with a decrease in the number of cases (p-value < 0.05), which might be directly related to health literacy and compliance with public health measures. These features indicate that social distancing, protecting older adults, and vulnerable populations, as well as promoting health literacy, might be useful to reduce SARS-CoV-2 spread in Iran. One limitation of our analysis is that the most updated information we found concerning socioeconomic and climatic features is not for 2020, or even for a same year, so that the obtained associations should be interpreted with caution. Our approach could be applied to model COVID-19 outbreaks in other countries with similar characteristics or in case of an upturn in COVID-19 within Iran.

No abstract

Prolactin (PRL) is a peptidic hormone that displays pleiotropic functions in the organism including different actions in the brain. PRL exerts a neuroprotective effect against excitotoxicity produced by glutamate (Glu) or kainic acid in both in vitro and in vivo models. It is well known that Glu excitotoxicity causes cell death through apoptotic or necrotic pathways due to intracellular calcium ([Ca2+] i) overload. Therefore, the aim of the present study was to assess the molecular mechanisms by which PRL maintains cellular viability of primary cultures of rat hippocampal neurons exposed to Glu excitotoxicity. We determined cell viability by monitoring mitochondrial activity and using fluorescent markers for viable and dead cells. The intracellular calcium level was determined by a fluorometric assay and proteins involved in the apoptotic pathway were determined by immunoblot. Our results demonstrated that PRL afforded neuroprotection against Glu excitotoxicity, as evidenced by a decrease in propidium iodide staining and by the decrease of the LDH activity. In addition, the MTT assay shows that PRL maintains normal mitochondrial activity even in neurons exposed to Glu. Furthermore, the Glu-induced intracellular [Ca2+]i overload was attenuated by PRL. These data correlate with the reduction found in the level of active caspase-3 and the pro-apoptotic ratio (Bax/Bcl-2). Concomitantly, PRL elicited the nuclear translocation of the transcriptional factor NF-κB, which was detected by immunofluorescence and confocal microscopy. To our knowledge, this is the first report demonstrating that PRL prevents Glu excitotoxicity by a mechanism involving the restoration of the intracellular calcium homeostasis and mitochondrial activity, as well as an anti-apoptotic action possibly mediated by the activity of NF-κB. Overall, the current results suggest that PRL could be of potential therapeutic advantage in the treatment of neurodegenerative diseases.

Human macrophage migration inhibitory factor (MIF) is a cytokine that plays a role in several metabolic and inflammatory processes. Single nucleotide polymorphism (SNP) -173 G/C (rs755622) on MIF gene has been associated with numerous diseases, such as arthritis and cancer. However, most of the reports concerning the association of MIF with these and other pathologies are inconsistent and remain quite controversial. Therefore, we performed a meta-analysis from 96 case-control studies on -173 G/C MIF SNP and stratified the data according to the subjects geographic localization or the disease pathophysiology, in order to determine a more meaningful significance to this SNP. The polymorphism was strongly associated with an increased risk in autoimmune-inflammatory, infectious and age-related diseases on the dominant (OR: 0.74 [0.58–0.93], P < 0.01; OR: 0.81 [0.74–0.89], P < 0.0001; and OR: 0.81 [0.76–0.87], P < 0.0001, respectively) and the recessive models (OR: 0.74 [0.57–0.095], P < 0.01; OR: 0.66 [0.48–0.92], P < 0.0154; and OR: 0.70 [0.60–0.82], P < 0.0001, respectively). Also, significant association was found in the geographic localization setting for Asia, Europe and Latin America subdivisions in the dominant (OR: 0.76 [0.69–0.84], P < 0.0001; OR: 0.77 [0.72–0.83], P < 0.0001; OR: 0.61 [0.44–0.83], P-value: 0.0017, respectively) and overdominant models (OR: 0.85 [0.77–0.94], P < 0.0001; OR: 0.80 [0.75–0.86], P < 0.0001; OR: 0.73 [0.63–0.85], P-value: 0.0017, respectively). Afterwards, we implemented a network meta-analysis to compare the association of the polymorphism for two different subdivisions. We found a stronger association for autoimmune than for age-related or autoimmune-inflammatory diseases, and stronger association for infectious than for autoimmune-inflammatory diseases. We report for the first time a meta-analysis of rs755622 polymorphism with a variety of stratified diseases and populations. The study reveals a strong association of the polymorphism with autoimmune and infectious diseases. These results may help direct future research on MIF-173 G/C in diseases in which the relation is clearer and thus assist the search for more plausible applications.

No abstract