Gut Microbiota Dynamics in Natural Populations of Pintomyia evansi under Experimental Infection with Leishmania infantum

Pintomyia evansi is recognized by its vectorial competence in the transmission of parasites that cause fatal visceral leishmaniasis in rural and urban environments of the Caribbean coast of Colombia. The effect on and the variation of the gut microbiota in female P. evansi infected with Leishmania infantum were evaluated under experimental conditions using 16S rRNA Illumina MiSeq sequencing. In the coinfection assay with L. infantum, 96.8% of the midgut microbial population was composed mainly of Proteobacteria (71.0%), followed by Cyanobacteria (20.4%), Actinobacteria (2.7%), and Firmicutes (2.7%). In insect controls (uninfected with L. infantum) that were treated or not with antibiotics, Ralstonia was reported to have high relative abundance (55.1–64.8%), in contrast to guts with a high load of infection from L. infantum (23.4–35.9%). ASVs that moderately increased in guts infected with Leishmania were Bacillus and Aeromonas. Kruskal–Wallis nonparametric variance statistical inference showed statistically significant intergroup differences in the guts of P. evansi infected and uninfected with L. infantum (p < 0.05), suggesting that some individuals of the microbiota could induce or restrict Leishmania infection. This assay also showed a negative effect of the antibiotic treatment and L. infantum infection on the gut microbiota diversity. Endosymbionts, such as Microsporidia infections (<2%), were more often associated with guts without Leishmania infection, whereas Arsenophonus was only found in guts with a high load of Leishmania infection and treated with antibiotics. Finally, this is the first report that showed the potential role of intestinal microbiota in natural populations of P. evansi in susceptibility to L. infantum infection.

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Gut Microbiome in a Russian Cohort of Pre- and Post-Cholecystectomy Female Patients

Journal of Personalized Medicine ◽

10.3390/jpm11040294 ◽

2021 ◽

Vol 11 (4) ◽

pp. 294

Author(s):

Irina Grigor’eva ◽

Tatiana Romanova ◽

Natalia Naumova ◽

Tatiana Alikina ◽

Alexey Kuznetsov ◽

...

Keyword(s):

Gut Microbiota ◽

Relative Abundance ◽

Gut Microbiome ◽

Gallstone Disease ◽

Illumina Miseq ◽

Rrna Gene ◽

Bacterial Phyla ◽

Female Patients ◽

Composition And Structure ◽

Before And After

The last decade saw extensive studies of the human gut microbiome and its relationship to specific diseases, including gallstone disease (GSD). The information about the gut microbiome in GSD-afflicted Russian patients is scarce, despite the increasing GSD incidence worldwide. Although the gut microbiota was described in some GSD cohorts, little is known regarding the gut microbiome before and after cholecystectomy (CCE). By using Illumina MiSeq sequencing of 16S rRNA gene amplicons, we inventoried the fecal bacteriobiome composition and structure in GSD-afflicted females, seeking to reveal associations with age, BMI and some blood biochemistry. Overall, 11 bacterial phyla were identified, containing 916 operational taxonomic units (OTUs). The fecal bacteriobiome was dominated by Firmicutes (66% relative abundance), followed by Bacteroidetes (19%), Actinobacteria (8%) and Proteobacteria (4%) phyla. Most (97%) of the OTUs were minor or rare species with ≤1% relative abundance. Prevotella and Enterocossus were linked to blood bilirubin. Some taxa had differential pre- and post-CCE abundance, despite the very short time (1–3 days) elapsed after CCE. The detailed description of the bacteriobiome in pre-CCE female patients suggests bacterial foci for further research to elucidate the gut microbiota and GSD relationship and has potentially important biological and medical implications regarding gut bacteria involvement in the increased GSD incidence rate in females.

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Rurality and Party System Fragmentation in the Nigerian Presidential Elections of the Fourth Republic

Statistics Politics and Policy ◽

10.1515/spp-2019-0007 ◽

2020 ◽

Vol 11 (1) ◽

pp. 59-85

Author(s):

Cletus Famous Nwankwo

Keyword(s):

Presidential Elections ◽

Party System ◽

Party Systems ◽

Voting Behaviour ◽

Composite Measure ◽

Singular Measures ◽

Rural And Urban ◽

Fourth Republic ◽

Cast Doubt ◽

Negative Effect

AbstractThis paper examines the effect of rurality on party system fragmentation in the Nigerian presidential elections of the fourth republic. The findings show that party system fragmentation (PSF) has been characteristically low in the Nigerian presidential elections and rurality does not significantly predict party system fragmentation. Rurality has a negative effect on PSF in all the elections studied except the 2003 election but only significant in the 2011 poll. Thus, the paper cast doubt on previous studies that indicate that striking rural-urban differences manifest in party system fragmentation in African elections and attribute it to previous studies’ measure of rurality. The paper argues that the use of a composite measure of rurality instead of singular measures of rurality might provide better analysis that helps us understand the effect of rurality on party systems. Also, it argues that in the study of the rural-urban difference in voting behaviour or political behaviours more broadly, data should be aggregated based on cities and non-city areas because cities have distinctive urban characters compared with non-city places. Analyses done on states or constituencies level may not reveal the rural-urban difference because states and constituencies usually have a mix of rural and urban population and other characteristics.

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Comparison between 16S rRNA and shotgun sequencing data for the taxonomic characterization of the gut microbiota

Scientific Reports ◽

10.1038/s41598-021-82726-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Francesco Durazzi ◽

Claudia Sala ◽

Gastone Castellani ◽

Gerardo Manfreda ◽

Daniel Remondini ◽

...

Keyword(s):

16S Rrna ◽

Gut Microbiota ◽

16S Rrna Gene ◽

Gene Sequencing ◽

16S Rrna Gene Sequencing ◽

Shotgun Sequencing ◽

Rrna Gene ◽

Metagenomic Sequencing ◽

Experimental Conditions ◽

Rrna Gene Sequencing

AbstractIn this paper we compared taxonomic results obtained by metataxonomics (16S rRNA gene sequencing) and metagenomics (whole shotgun metagenomic sequencing) to investigate their reliability for bacteria profiling, studying the chicken gut as a model system. The experimental conditions included two compartments of gastrointestinal tracts and two sampling times. We compared the relative abundance distributions obtained with the two sequencing strategies and then tested their capability to distinguish the experimental conditions. The results showed that 16S rRNA gene sequencing detects only part of the gut microbiota community revealed by shotgun sequencing. Specifically, when a sufficient number of reads is available, Shotgun sequencing has more power to identify less abundant taxa than 16S sequencing. Finally, we showed that the less abundant genera detected only by shotgun sequencing are biologically meaningful, being able to discriminate between the experimental conditions as much as the more abundant genera detected by both sequencing strategies.

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You are what you eat: relative importance of diet, gut microbiota and nestmates for honey bee, Apis mellifera, worker health

Apidologie ◽

10.1007/s13592-021-00851-z ◽

2021 ◽

Author(s):

Gina Retschnig ◽

Johannes Rich ◽

Karl Crailsheim ◽

Judith Pfister ◽

Vincent Perreten ◽

...

Keyword(s):

Body Weight ◽

Apis Mellifera ◽

Gut Microbiota ◽

Honey Bee ◽

Exposure Period ◽

Short Exposure ◽

Relative Importance ◽

Worker Health ◽

Negative Effect ◽

Positive Effect

AbstractIn eusocial honey bees, Apis mellifera, diet, gut microbiota and nestmates can all contribute to the health of freshly emerged individual workers, but their relative importance for longevity and body weight is currently unknown. Here, we show that diet is most relevant, followed by gut microbiota and the presence of nestmates. Freshly emerged workers were randomly assigned to eight treatments (with or without honey/pollen, protein-substitute lactalbumin, antibiotic tetracycline and nestmates for 24 h) and maintained under standardised laboratory conditions. Longevity and food consumption were measured daily and fresh body weight was assessed at day 7. The data show a significantly better survival and a higher body weight in workers supplied with honey/pollen. Survival was higher in the lactalbumin treatments compared to the ones restricted to sucrose only, but lower compared to those with honey/pollen, highlighting the importance of micronutrients. In contrast, antibiotic treatment had a significant negative effect on longevity and body weight, which may be explained by inactivated gut microbiota and/or toxicity of the antibiotics. There was no positive effect of nestmates, probably due to the short exposure period. In contrast, nestmates showed a negative effect on survival in antibiotic-treated workers, possibly by transmitting pathogens and antibiotic-induced gut dysbiosis. In conclusion, a macro- and micronutrient-rich diet appears to be the key to individual honey bee worker health. Providing an optimal diet and possibly gut microbiota appears to be a promising way to promote managed A. mellifera health.

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Effect of education on migration decisions in Ghana: a rural-urban perspective

Journal of Economic Studies ◽

10.1108/jes-09-2013-0138 ◽

2016 ◽

Vol 43 (2) ◽

pp. 336-356 ◽

Cited By ~ 5

Author(s):

Franklin Amuakwa-Mensah ◽

Louis Boakye-Yiadom ◽

William Baah-Boateng

Keyword(s):

Educational Attainment ◽

Rural Areas ◽

Migration Decision ◽

Skilled Workers ◽

Mixed Effect ◽

Content Type ◽

Rural And Urban ◽

Migration Decisions ◽

Negative Effect ◽

The Impact

Purpose – The purpose of this paper is to investigate the effect of education on migration decisions focusing on rural and urban in-migrants by comparing the 2005/2006 and 2012/2013 rounds of the Ghana Living Standards Survey (GLSS5 and GLSS6). After correcting for selectivity bias, the authors observed that anticipated welfare gain and socio-economic variables such as sector of employment, sex, experience, age, educational level and marital status significantly affect an individual’s migration decision. Design/methodology/approach – The authors made use of Sjaastad’s (1962) human capital framework as a basis for examining the impact of education on migration. The migration decision equation was based on the Heckman two stage procedure. Findings – While educational attainment is observed to have a positive effect on migration decision in the period 2005/2006, the authors find a negative effect of educational attainment on migration decision in the period 2012/2013. The effect of educational attainment on migration decision in 2005/2006 for urban in-migrant is higher than the effect for rural in-migrant, with its significance varying for the different stages of educational attainment. In absolute terms, whereas the effect of secondary educational attainment on migration decisions for urban in-migrant is higher than that of rural in-migrant, the reverse holds for higher educational attainment during the period 2012/2013. Social implications – Based on the mixed effect of education on migration decision as evident from the study, policies to enhance the educational system in Ghana should be complemented with job creations in the entire country. Moreover, special attention should be given to the rural sector in such a way that the jobs to be created in the sector do not require skilled workers. With quality education and job creation, the welfare of individuals living in urban and rural areas will be enhanced. Originality/value – In spite of the importance of education in migration decisions, there is scanty literature on the rural-urban dimension. To the best of the author’s knowledge there is no literature in the Ghanaian context which examines the rural and urban perspective of the impact of education on migration with a much recent data. Further, the author consider how the determinants of migration decision have changed over time focusing on rural and urban perspectives.

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The Impact of Sampling Season and Catching Site (Wild and Aquaculture) on Gut Microbiota Composition and Diversity of Nile Tilapia (Oreochromis niloticus)

Biology ◽

10.3390/biology10030180 ◽

2021 ◽

Vol 10 (3) ◽

pp. 180

Author(s):

Negash Kabtimer Bereded ◽

Getachew Beneberu Abebe ◽

Solomon Workneh Fanta ◽

Manuel Curto ◽

Herwig Waidbacher ◽

...

Keyword(s):

Gut Microbiota ◽

Nile Tilapia ◽

Alpha Diversity ◽

Environmental Parameters ◽

Illumina Miseq ◽

Microbial Composition ◽

Lake Tana ◽

Future Work ◽

The Impact ◽

Sampling Season

The gut microbiota of fishes is known to play an essential role in diverse aspects of host biology. The gut microbiota of fish is affected by various environmental parameters, including temperature changes, salinity and diet. Studies of effect of environment on gut microbiota enables to have a further understanding of what comprises a healthy microbiota under different environmental conditions. However, there is insufficient understanding regarding the effects of sampling season and catching site (wild and aquaculture) on the gut microbiota of Nile tilapia. This study characterised gut microbial composition and diversity from samples collected from Lake Tana and the Bahir Dar aquaculture facility centre using 16S rDNA Illumina MiSeq platform sequencing. Firmicutes and Fusobacteria were the most dominant phyla in the Lake Tana samples, while Proteobacteria was the most dominant in the aquaculture samples. The results of differential abundance testing clearly indicated significant differences for Firmicutes, Fusobacteria, Bacteroidetes and Cyanobacteria across sampling months. However, Proteobacteria, Chloroflexi, Fusobacteria and Cyanobacteria were significantly enriched in the comparison of samples from the Lake Tana and aquaculture centre. Significant differences were observed in microbial diversity across sampling months and between wild and captive Nile tilapia. The alpha diversity clearly showed that samples from the aquaculture centre (captive) had a higher diversity than the wild Nile tilapia samples from Lake Tana. The core gut microbiota of all samples of Nile tilapia used in our study comprised Firmicutes, Proteobacteria and Fusobacteria. This study clearly showed the impact of sampling season and catching site (wild and aquaculture) on the diversity and composition of bacterial communities associated with the gut of Nile tilapia. Overall, this is the first study on the effects of sampling season and catching site on the gut microbiota of Nile tilapia in Ethiopia. Future work is recommended to precisely explain the causes of these changes using large representative samples of Nile tilapia from different lakes and aquaculture farms.

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Damage assessment mapping of rural environments; integration of SAR and Optical data

10.5194/egusphere-egu21-9202 ◽

2021 ◽

Author(s):

Shiran Havivi ◽

Stanley R. Rotman ◽

Dan G. Blumberg ◽

Shimrit Maman

Keyword(s):

Natural Disaster ◽

Rural Areas ◽

Urban Areas ◽

Damage Assessment ◽

Vegetation Index ◽

Urban Environments ◽

Optical Data ◽

Damage Level ◽

Rural Environments ◽

Rural And Urban

The damage caused by a natural disaster in rural areas differs in nature, extent, landscape and in structure, from the damage in urban environments. Previous and current studies focus mainly on mapping damaged structures in urban areas after catastrophe events such as an earthquake or tsunami. Yet, research focusing on the damage level or its distribution in rural areas is absent. In order to apply an emergency response and for effective disaster management, it is necessary to understand and characterize the nature of the damage in each different environment.&#160;Havivi et al. (2018), published a damage assessment algorithm that makes use of SAR images combined with optical data, for rapid mapping and compiling a damage assessment map following a natural disaster. The affected areas are analyzed using interferometric SAR (InSAR) coherence. To overcome the loss of coherence caused by changes in vegetation, optical images are used to produce a mask by computing the Normalized Difference Vegetation Index (NDVI) and removing the vegetated area from the scene. Due to the differences in geomorphological settings and landuse\landcover between rural and urban settlements, the above algorithm is modified and adjusted by inserting the Modified Normalized Difference Water Index (MNDWI) to better suit rural environments and their unique response after a disaster. MNDWI is used for detection, identification and extraction of waterbodies (such as irrigation canals, streams, rivers, lakes, etc.), allowing their removal which causes lack of coherence at the post stage of the event. Furthermore, it is used as an indicator for highlighting prone regions that might be severely affected pre disaster event. Thresholds are determined for the co-event coherence map (&#8804; 0.5), the NDVI (&#8805; 0.4) and the MNDWI (&#8805; 0), and the three layers are combined into one. Based on the combined map, a damage assessment map is generated.&#160;As a case study, this algorithm was applied to the areas affected by multi-hazard event, following the Sulawesi earthquake and subsequent tsunami in Palu, Indonesia, which occurred on September 28th, 2018. High-resolution COSMO-SkyMed images pre and post the event, alongside a Sentinel-2 image pre- event are used as inputs. The output damage assessment map provides a quantitative assessment and spatial distribution of the damage in both the rural and urban environments. The results highlight the applicability of the algorithm for a variety of disaster events and sensors. In addition, the results enhance the contribution of the water component to the analysis pre and post the event in rural areas. Thus, while in urban regions the spatial extent of the damage will occur in its proximity to the coastline or the fault, rural regions, even in significant distance will experience extensive damage due secondary hazards as liquefaction processes.&#160; &#160; &#160;

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Leishmania infection in bats from a non-endemic region of Leishmaniasis in Brazil

Parasitology ◽

10.1017/s0031182017001500 ◽

2017 ◽

Vol 144 (14) ◽

pp. 1980-1986 ◽

Cited By ~ 6

Author(s):

CÉSAR GÓMEZ-HERNÁNDEZ ◽

ELAINE C. BENTO ◽

KARINE REZENDE-OLIVEIRA ◽

GABRIEL A. N. NASCENTES ◽

CECILIA G. BARBOSA ◽

...

Keyword(s):

Urban Areas ◽

Leishmania Infection ◽

Leishmania Braziliensis ◽

Endemic Region ◽

Blood Samples ◽

Rural And Urban Areas ◽

Rural And Urban ◽

Minas Gerais State ◽

Close Relationship ◽

Epidemiological Significance

SUMMARYLeishmaniasis is a complex of zoonotic diseases caused by parasites of the genus Leishmania, which can develop in domestic as well as wild animals and humans throughout the world. Currently, this disease is spreading in rural and urban areas of non-endemic regions in Brazil. Recently, bats have gained epidemiological significance in leishmaniasis due to its close relationship with human settlements. In this study, we investigated the presence of Leishmania spp. DNA in blood samples from 448 bats belonging to four families representing 20 species that were captured in the Triangulo Mineiro and Alto Paranaiba areas of Minas Gerais State (non-endemic areas for leishmaniasis), Brazil. Leishmania spp. DNA was detected in 8·0% of the blood samples, 41·6% of which were Leishmania infantum, 38·9% Leishmania amazonensis and 19·4% Leishmania braziliensis. No positive correlation was found between Leishmania spp. and bat food source. The species with more infection rates were the insectivorous bats Eumops perotis; 22·2% (4/18) of which tested positive for Leishmania DNA. The presence of Leishmania in the bat blood samples, as observed in this study, represents epidemiological importance due to the absence of Leishmaniasis cases in the region.

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Bounding the Practical Error of Path Loss Models

International Journal of Antennas and Propagation ◽

10.1155/2012/754158 ◽

2012 ◽

Vol 2012 ◽

pp. 1-21 ◽

Cited By ~ 17

Author(s):

Caleb Phillips ◽

Douglas Sicker ◽

Dirk Grunwald

Keyword(s):

A Priori ◽

Path Loss ◽

Urban Environments ◽

Production Networks ◽

Modeling Error ◽

Propagation Models ◽

Performance Accuracy ◽

Rural And Urban ◽

Standard Models ◽

Loss Models

We seek to provide practical lower bounds on the prediction accuracy of path loss models. We describe and implement 30 propagation models of varying popularity that have been proposed over the last 70 years. Our analysis is performed using a large corpus of measurements collected on production networks operating in the 2.4 GHz ISM, 5.8 GHz UNII, and 900 MHz ISM bands in a diverse set of rural and urban environments. We find that the landscape of path loss models is precarious: typical best-case performance accuracy of these models is on the order of 12–15 dB root mean square error (RMSE) and in practice it can be much worse. Models that can be tuned with measurements and explicit data fitting approaches enable a reduction in RMSE to 8-9 dB. These bounds on modeling error appear to be relatively constant, even in differing environments and at differing frequencies. Based on our findings, we recommend the use of a few well-accepted and well-performing standard models in scenarios wherea prioripredictions are needed and argue for the use of well-validated, measurement-driven methods whenever possible.

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Evidence and theory for lower rates of depression in larger US urban areas

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2022472118 ◽

2021 ◽

Vol 118 (31) ◽

pp. e2022472118

Author(s):

Andrew J. Stier ◽

Kathryn E. Schertz ◽

Nak Won Rim ◽

Carlos Cardenas-Iniguez ◽

Benjamin B. Lahey ◽

...

Keyword(s):

Mental Health ◽

Social Networks ◽

Social Determinants ◽

Urban Areas ◽

Urban Environments ◽

City Size ◽

Built Environments ◽

Rural And Urban ◽

Us Cities ◽

Systematic Framework

It is commonly assumed that cities are detrimental to mental health. However, the evidence remains inconsistent and at most, makes the case for differences between rural and urban environments as a whole. Here, we propose a model of depression driven by an individual’s accumulated experience mediated by social networks. The connection between observed systematic variations in socioeconomic networks and built environments with city size provides a link between urbanization and mental health. Surprisingly, this model predicts lower depression rates in larger cities. We confirm this prediction for US cities using four independent datasets. These results are consistent with other behaviors associated with denser socioeconomic networks and suggest that larger cities provide a buffer against depression. This approach introduces a systematic framework for conceptualizing and modeling mental health in complex physical and social networks, producing testable predictions for environmental and social determinants of mental health also applicable to other psychopathologies.

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