Mouse dendritic cells in the steady state: Hypoxia, autophagy, and stem cell factor

Dendritic cells (DCs) are innate immune cells with a central role in immunity and tolerance. Under steady-state, DCs are scattered in tissues as resting cells. Upon infection or injury, DCs get activated and acquire the full capacity to prime antigen-specific CD4(+) and CD8(+) T cells, thus bridging innate and adaptive immunity. By secreting different sets of cytokines and chemokines, DCs orchestrate diverse types of immune responses, from a classical proinflammatory to an alternative pro-repair one. DCs are highly heterogeneous, and physiological differences in tissue microenvironments greatly contribute to variations in DC phenotype. Oxygen tension is normally low in some lymphoid areas, including bone marrow (BM) hematopoietic niches; nevertheless, the possible impact of tissue hypoxia on DC physiology has been poorly investigated. We assessed whether DCs are hypoxic in BM and spleen, by staining for hypoxia-inducible-factor-1 alpha subunit (HIF-1 alpha), the master regulator of hypoxia-induced response, and pimonidazole (PIM), a hypoxic marker, and by flow cytometric analysis. Indeed, we observed that mouse DCs have a hypoxic phenotype in spleen and BM, and showed some remarkable differences between DC subsets. Notably, DCs expressing membrane c-kit, the receptor for stem cell factor (SCF), had a higher PIM median fluorescence intensity (MFI) than c-kit(-) DCs, both in the spleen and in the BM. To determine whether SCF (a.k.a. kit ligand) has a role in DC hypoxia, we evaluated molecular pathways activated by SCF in c-kit(+) BM-derived DCs cultured in hypoxic conditions. Gene expression microarrays and gene set enrichment analysis supported the hypothesis that SCF had an impact on hypoxia response and inhibited autophagy-related gene sets. Our results suggest that hypoxic response and autophagy, and their modulation by SCF, can play a role in DC homeostasis at the steady state, in agreement with our previous findings on SCF's role in DC survival

Re-emergence of human leishmaniasis in northern Italy, 2004 to 2022: a retrospective analysis

Background. Human leishmaniasis is a protozoan disease transmitted by sand flies and endemic in the Mediterranean region. In Italy, leishmaniasis is present in the south and the western coastal regions, with an epidemic peak detected in northern Italy in the early 1970s.AimTo examine temporal trends, and demographic, clinical, geographical and environmental features of human leishmaniasis cases recorded by the local health unit (LHU) of Bologna, northern Italy.MethodsIn this retrospective observational study, we analysed human leishmaniasis cases recorded from 2004 to 2022 within the Bologna LHU. We also conducted serological investigations for canine leishmaniasis in owned dogs living near the place of infection of human cases. Results. In total, 173 cases of human leishmaniasis were detected, and 154 cases were considered autochthonous. An increase of human cases was observed since 2004, with incidence peaks above 2 cases/100,000 inhabitants in 2013, 2018 and 2022; epidemic peaks were preceded by dry summers. Most cases lived in the plain and hilly areas less than 400 m above sea level and many resided in isolated housing, in city outskirts, and/or near uncultivated areas, watercourses and railway sections. The incidence of canine leishmaniasis did not increase in the study period.Conclusion. An epidemic of human leishmaniasis with fluctuating annual numbers of cases, probably related to environmental and climatic factors, was identified in the Bologna LHU. Understanding the risk factors and the environmental characteristics related to places of infection is crucial to evaluate the public health implications of leishmaniasis

Mosquito, Bird and Human Surveillance of West Nile and Usutu Viruses in Emilia-Romagna Region (Italy) in 2010

<div><h3>Background</h3><p>In 2008, after the first West Nile virus (WNV) detection in the Emilia-Romagna region, a surveillance system, including mosquito- and bird-based surveillance, was established to evaluate the virus presence. Surveillance was improved in following years by extending the monitoring to larger areas and increasing the numbers of mosquitoes and birds tested.</p> <h3>Methodology/Principal Findings</h3><p>A network of mosquito traps, evenly distributed and regularly activated, was set up within the surveyed area. A total of 438,558 mosquitoes, grouped in 3,111 pools and 1,276 birds (1,130 actively sampled and 146 from passive surveillance), were tested by biomolecular analysis. The survey detected WNV in 3 <em>Culex pipiens</em> pools while Usutu virus (USUV) was found in 89 <em>Cx. pipiens</em> pools and in 2 <em>Aedes albopictus</em> pools. Two birds were WNV-positive and 12 were USUV-positive. Furthermore, 30 human cases of acute meningoencephalitis, possibly caused by WNV or USUV, were evaluated for both viruses and 1,053 blood bags were tested for WNV, without any positive result.</p> <h3>Conclusions/Significance</h3><p>Despite not finding symptomatic human WNV infections during 2010, the persistence of the virus, probably due to overwintering, was confirmed through viral circulation in mosquitoes and birds, as well as for USUV. In 2010, circulation of the two viruses was lower and more delayed than in 2009, but this decrease was not explained by the relative abundance of <em>Cx. pipiens</em> mosquito, which was greater in 2010. The USUV detection in mosquito species confirms the role of <em>Cx. pipiens</em> as the main vector and the possible involvement of <em>Ae. albopictus</em> in the virus cycle. The effects of meteorological conditions on the presence of USUV-positive mosquito pools were considered finding an association with drought conditions and a wide temperature range. The output produced by the surveillance system demonstrated its usefulness and reliability in terms of planning public health policies.</p> </div

West Nile virus transmission. results from the integrated surveillance system in Italy, 2008 to 2015

IIn Italy a national Plan for the surveillance of imported and autochthonous human vector-borne diseases (chikungunya, dengue, Zika virus disease and West Nile virus (WNV) disease) that integrates human and veterinary (animals and vectors) surveillance, is issued and revised annually according with the observed epidemiological changes. Here we describe results of the WNV integrated veterinary and human surveillance systems in Italy from 2008 to 2015. A real time data exchange protocol is in place between the surveillance systems to rapidly identify occurrence of human and animal cases and to define and update the map of affected areas i.e. provinces during the vector activity period from June to October. WNV continues to cause severe illnesses in Italy during every transmission season, albeit cases are sporadic and the epidemiology varies by virus lineage and geographic area. The integration of surveillance activities and a multidisciplinary approach made it possible and have been fundamental in supporting implementation of and/or strengthening preventive measures aimed at reducing the risk of transmission of WNV trough blood, tissues and organ donation and to implementing further measures for vector control

Epidemiological modelling for the assessment of bovine tuberculosis surveillance in the dairy farm network in Emilia-Romagna (Italy)

Assessing the performance of a surveillance system for infectious diseases of domestic animals is a challenging task for health authorities. Therefore, it is important to assess what strategy is the most effective in identifying the onset of an epidemic and in minimizing the number of infected farms. The aim of the present work was to evaluate the performance of the bovine tuberculosis (bTB) surveillance system in the network of dairy farms in the Emilia-Romagna (ER) Region, Italy. A bTB-free Region since 2007, ER implements an integrated surveillance strategy based on three components, namely routine on-farm tuberculin skin-testing performed every 3 years, tuberculin skin-testing of cattle exchanged between farms, and post-mortem inspection at slaughterhouses. We assessed the effectiveness of surveillance by means of a stochastic network model of both within-farm and between-farm bTB dynamics calibrated on data available for ER dairy farms. Epidemic dynamics were simulated for five scenarios: the current ER surveillance system, a no surveillance scenario that we used as the benchmark to characterize epidemic dynamics, three additional scenarios in which one of the surveillance components was removed at a time so as to outline its significance in detecting the infection. For each scenario we ran Monte Carlo simulations of bTB epidemics following the random introduction of an infected individual in the network. System performances were assessed through the comparative analysis of a number of statistics, including the time required for epidemic detection and the total number of infected farms during the epidemic. Our analysis showed that slaughterhouse inspection is the most effective surveillance component in reducing the time for disease detection, while routine surveillance in reducing the number of multi-farms epidemics. On the other hand, testing exchanged cattle improved the performance of the surveillance system only marginally

The Potential Role of Direct and Indirect Contacts on Infection Spread in Dairy Farm Networks

<div><p>Animals’ exchanges are considered the most effective route of between-farm infectious disease transmission. However, despite being often overlooked, the infection spread due to contaminated equipment, vehicles, or personnel proved to be important for several livestock epidemics. This study investigated the role of indirect contacts in a potential infection spread in the dairy farm network of the Province of Parma (Northern Italy). We built between-farm contact networks using data on cattle exchange (direct contacts), and on-farm visits by veterinarians (indirect contacts). We compared the features of the contact structures by using measures on static and temporal networks. We assessed the disease spreading potential of the direct and indirect network structures in the farm system by using data on the infection state of farms by paratuberculosis. Direct and indirect networks showed non-trivial differences with respect to connectivity, contact distribution, and super-spreaders identification. Furthermore, our analyses on paratuberculosis data suggested that the contributions of direct and indirect contacts on diseases spread are apparent at different spatial scales. Our results highlighted the potential role of indirect contacts in between-farm disease spread and underlined the need for a deeper understanding of these contacts to develop better strategies for prevention of livestock epidemics.</p></div

Multilocus microsatellite typing (MLMT) reveals host-related population structure in Leishmania infantum from northeastern Italy.

BACKGROUND:Visceral leishmaniasis (VL) caused by Leishmania infantum is an ongoing health problem in southern Europe, where dogs are considered the main reservoirs of the disease. Current data point to a northward spread of VL and canine leishmaniasis (CanL) in Italy, with new foci in northern regions previously regarded as non-endemic. METHODOLOGY/PRINCIPAL FINDINGS:Multilocus microsatellite typing (MLMT) was performed to investigate genetic diversity and population structure of L. infantum on 55 samples from infected humans, dogs and sand flies of the E-R region between 2013 and 2017. E-R samples were compared with 10 L. infantum samples from VL cases in other Italian regions (extra E-R) and with 52 strains within the L. donovani complex. Data displayed significant microsatellite polymorphisms with low allelic heterozygosity. Forty-one unique and eight repeated MLMT profiles were recognized among the L. infantum samples from E-R, and ten unique MLMT profiles were assigned to the extra E-R samples. Bayesian analysis assigned E-R samples to two distinct populations, with further sub-structuring within each of them; all CanL samples belonged to one population, genetically related to Mediterranean MON-1 strains, while all but one VL cases as well as the isolate from the sand fly Phlebotomus perfiliewi fell under the second population. Conversely, VL samples from other Italian regions proved to be genetically similar to strains circulating in dogs. CONCLUSIONS/SIGNIFICANCE:A peculiar epidemiological situation was observed in northeastern Italy, with the co-circulation of two distinct populations of L. infantum; one population mainly detected in dogs and the other population detected in humans and in a sand fly. While the classical cycle of CanL in Italy fits well into the data obtained for the first population, the population found in infected humans exhibits a different cycle, probably not involving a canine reservoir. This study can contribute to a better understanding of the population structure of L. infantum circulating in northeastern Italy, thus providing useful epidemiologic information for public health authorities

MAP spatial distribution.

<p>Spatial distribution of the infection state of farms by <i>Mycobacterium avium</i> subsp. <i>paratuberculosis</i> (MAP) in the Province of Parma. Black dots correspond to infected farms; dark-grey circles to non-infected farms; and small light-grey dots to no-data farms.</p

Farm exposure to MAP infection.

<p>Mean exposure to MAP-positive (blue dots, <i>E</i>_<i>I</i>) and MAP-negative (red dots, <i>E</i>_<i>S</i>) farms normalized between zero and one in: upper) cattle movements network (CM) of Emilia-Romagna region (i.e. regional scale); middle) cattle movement network of Parma Province (i.e. local scale); and bottom) the veterinary network (VT) of Parma Province. Vertical bars represent the mean exposure to MAP in random networks with the same distribution of farm contacts as in the observed networks.</p

<i>q</i>-nearest neighbours test.

<p>Results of the <i>q</i>-nearest neighbours test on the infection state of farms by <i>Mycobacterium avium</i> subsp. <i>paratuberculosis</i> (MAP) within the dairy farms of the Province of Parma. Columns show the number <i>q</i>-nearest neighbours selected for the analysis (i.e. total number of cases within the number of <i>q</i> neighbours of each farm within the system) and corresponding p-value (<i>p</i>).</p