MyMedR

Displaying all 3 publications

Abstract:

Sort:

Fulltext Detection of mitochondrial COII DNA sequences in ant guts as a method for assessing termite predation by ants

Fayle TM, Scholtz O, Dumbrell AJ, Russell S, Segar ST, Eggleton P

PLoS One, 2015;10(4):e0122533.
PMID: 25853549 DOI: 10.1371/journal.pone.0122533

Termites and ants contribute more to animal biomass in tropical rain forests than any other single group and perform vital ecosystem functions. Although ants prey on termites, at the community level the linkage between these groups is poorly understood. Thus, assessing the distribution and specificity of ant termitophagy is of considerable interest. We describe an approach for quantifying ant-termite food webs by sequencing termite DNA (cytochrome c oxidase subunit II, COII) from ant guts and apply this to a soil-dwelling ant community from tropical rain forest in Gabon. We extracted DNA from 215 ants from 15 species. Of these, 17.2 % of individuals had termite DNA in their guts, with BLAST analysis confirming the identity of 34.1 % of these termites to family level or better. Although ant species varied in detection of termite DNA, ranging from 63 % (5/7; Camponotus sp. 1) to 0 % (0/7; Ponera sp. 1), there was no evidence (with small sample sizes) for heterogeneity in termite consumption across ant taxa, and no evidence for species-specific ant-termite predation. In all three ant species with identifiable termite DNA in multiple individuals, multiple termite species were represented. Furthermore, the two termite species that were detected on multiple occasions in ant guts were in both cases found in multiple ant species, suggesting that ant-termite food webs are not strongly compartmentalised. However, two ant species were found to consume only Anoplotermes-group termites, indicating possible predatory specialisation at a higher taxonomic level. Using a laboratory feeding test, we were able to detect termite COII sequences in ant guts up to 2 h after feeding, indicating that our method only detects recent feeding events. Our data provide tentative support for the hypothesis that unspecialised termite predation by ants is widespread and highlight the use of molecular approaches for future studies of ant-termite food webs.

Matched MeSH terms: Gabon
Fulltext Association between the spread of COVID-19 and weather-climatic parameters

Carta MG, Scano A, Lindert J, Bonanno S, Rinaldi L, Fais S, et al.

Eur Rev Med Pharmacol Sci, 2020 08;24(15):8226-8231.
PMID: 32767354 DOI: 10.26355/eurrev_202008_22512

OBJECTIVE: To explore whether the climate has played a role in the COVID-19 outbreak, we compared virus lethality in countries closer to the Equator with others. Lethality in European territories and in territories of some nations with a non-temperate climate was also compared.
MATERIALS AND METHODS: Lethality was calculated as the rate of deaths in a determinate moment from the outbreak of the pandemic out of the total of identified positives for COVID-19 in a given area/nation, based on the COVID-John Hopkins University website. Lethality of countries located within the 5th parallels North/South on 6 April and 6 May 2020, was compared with that of all the other countries. Lethality in the European areas of The Netherlands, France and the United Kingdom was also compared to the territories of the same nations in areas with a non-temperate climate.
RESULTS: A lower lethality rate of COVID-19 was found in Equatorial countries both on April 6 (OR=0.72 CI 95% 0.66-0.80) and on May 6 (OR=0.48, CI 95% 0.47-0.51), with a strengthening over time of the protective effect. A trend of higher risk in European vs. non-temperate areas was found on April 6, but a clear difference was evident one month later: France (OR=0.13, CI 95% 0.10-0.18), The Netherlands (OR=0.5, CI 95% 0.3-0.9) and the UK (OR=0.2, CI 95% 0.01-0.51). This result does not seem to be totally related to the differences in age distribution of different sites.
CONCLUSIONS: The study does not seem to exclude that the lethality of COVID-19 may be climate sensitive. Future studies will have to confirm these clues, due to potential confounding factors, such as pollution, population age, and exposure to malaria.

Matched MeSH terms: Gabon/epidemiology
Fulltext Co-distribution and co-infection of chikungunya and dengue viruses

Furuya-Kanamori L, Liang S, Milinovich G, Soares Magalhaes RJ, Clements AC, Hu W, et al.

BMC Infect Dis, 2016;16:84.
PMID: 26936191 DOI: 10.1186/s12879-016-1417-2

BACKGROUND: Chikungunya and dengue infections are spatio-temporally related. The current review aims to determine the geographic limits of chikungunya, dengue and the principal mosquito vectors for both viruses and to synthesise current epidemiological understanding of their co-distribution.
METHODS: Three biomedical databases (PubMed, Scopus and Web of Science) were searched from their inception until May 2015 for studies that reported concurrent detection of chikungunya and dengue viruses in the same patient. Additionally, data from WHO, CDC and Healthmap alerts were extracted to create up-to-date global distribution maps for both dengue and chikungunya.
RESULTS: Evidence for chikungunya-dengue co-infection has been found in Angola, Gabon, India, Madagascar, Malaysia, Myanmar, Nigeria, Saint Martin, Singapore, Sri Lanka, Tanzania, Thailand and Yemen; these constitute only 13 out of the 98 countries/territories where both chikungunya and dengue epidemic/endemic transmission have been reported.
CONCLUSIONS: Understanding the true extent of chikungunya-dengue co-infection is hampered by current diagnosis largely based on their similar symptoms. Heightened awareness of chikungunya among the public and public health practitioners in the advent of the ongoing outbreak in the Americas can be expected to improve diagnostic rigour. Maps generated from the newly compiled lists of the geographic distribution of both pathogens and vectors represent the current geographical limits of chikungunya and dengue, as well as the countries/territories at risk of future incursion by both viruses. These describe regions of co-endemicity in which lab-based diagnosis of suspected cases is of higher priority.
Erratum: Furuya-Kanamori L, Liang S, Milinovich G, Magalhaes RJ, Clements AC, Hu W, Brasil P, Frentiu FD, Dunning R, Yakob L. Erratum to: Co-distribution and co-infection of chikungunya and dengue viruses. BMC Infect Dis. 2016 Apr 29;16:188. doi: 10.1186/s12879-016-1519-x. PubMed PMID: 27129475; PubMed Central PMCID: PMC4851825.

Matched MeSH terms: Gabon

Filters

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links