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Molecular approaches supporting identification of Eimeria parasites infecting chickens have been available for more than 20 years, although they have largely failed to replace traditional measures such as microscopy and pathology. Limitations of microscopy-led diagnostics, including a requirement for specialist parasitological expertise and low sample throughput, are yet to be outweighed by the difficulties associated with accessing genomic DNA from environmental Eimeria samples. A key step towards the use of Eimeria species-specific PCR as a sensitive and reproducible discriminatory tool for use in the field is the production of a standardised protocol that includes sample collection and DNA template preparation, as well as primer selection from the numerous PCR assays now published. Such a protocol will facilitate development of valuable epidemiological datasets which may be easily compared between studies and laboratories. The outcome of an optimisation process undertaken in laboratories in India and the UK is described here, identifying four steps. First, samples were collected into a 2% (w/v) potassium dichromate solution. Second, oocysts were enriched by flotation in saturated saline. Third, genomic DNA was extracted using a QIAamp DNA Stool mini kit protocol including a mechanical homogenisation step. Finally, nested PCR was carried out using previously published primers targeting the internal transcribed spacer region 1 (ITS-1). Alternative methods tested included sample processing in the presence of faecal material, DNA extraction using a traditional phenol/chloroform protocol, the use of SCAR multiplex PCR (one tube and two tube versions) and speciation using the morphometric tool COCCIMORPH for the first time with field samples.

A total of 938 faecal samples (461 cattle calves, 264 buffalo calves, 55 lambs, 116 kids and 42 piglets) from different livestock farms and individual small holdings in six targeted states of India were collected and screened by modified Ziehl-Neelsen staining technique to determine the prevalence of Cryptosporidium spp. and its association with age, sex, season and faecal consistency in domesticated animals. Overall, 16.2 % of the animals were positive for Cryptosporidium infection with prevalence of 16.3, 24.2, 1.8, 3.5 and 19.1 % in cattle calves, buffalo calves, lambs, kids and piglets, respectively. The prevalence of infection was significantly higher (p<0.05) in bovines (19.3 % cattle and 33.7 % buffalo) below 1 month of age than in animals between 1 and 3 months of age. But in piglets, it was higher in the age group of 1 to 3 months (22.6 %) than in younger animals (9.1 %). Also, higher prevalence (p>0.05) was recorded in females than in males. Seasons had a significant effect (p<0.05) on the prevalence of infection in large ruminants, with the highest prevalence in monsoon (cattle 28.8 % and buffalo 36.6 %) followed by pre-monsoon and post-monsoon season. However, in case of sheep and goats, the prevalence was higher (p>0.05) in post-monsoon than in monsoon season. A high degree of association was noticed between Cryptosporidium infection and diarrhoea in ruminants screened during the present study. But, in case of pigs, the prevalence was higher in non-diarrhoeic than in diarrhoeic animals. Genotyping of Cryptosporidium spp. based on nested PCR amplification of partial 18S rRNA and its subsequent digestion with SspI, VspI and MboII restriction enzymes revealed prevalence of Cryptosporidium parvum in representative number of positive samples of cattle, buffalo and goats.

HighlightsMultivariate analysis revealed comparable poultry clusters in north and south India.Eimeria species occurrence varied between system clusters.E. tenella occurrence across systems may underpin region-specific genetic diversity.E. necatrix was found to be more common in north than south India.

We study the properties of 975 active galactic nuclei (AGN) selected by variability in the Pan-STARRS1 Medium-Deep Survey. Using complementary multi wavelength data from the ultraviolet to the far-infrared, we use SED fitting to determine the AGN and host properties at z < 1, and compare to a well-matched control sample. We confirm the trend previously observed that the variability amplitude decreases with AGN luminosity, but on the other hand, we observe that the slope of this relation steepens with wavelength resulting in a "redder when brighter" trend at low luminosities. Our results show that AGN are hosted by more massive hosts than control sample galaxies, while the restframe, dust-corrected N U V − r color distribution of AGN hosts is similar to control galaxies. We find a positive correlation between the AGN luminosity and star formation rate (SFR), independent of redshift. AGN hosts populate the whole range of SFRs within and outside the Main Sequence of star forming galaxies. Comparing the distribution of AGN hosts and control galaxies, we show that AGN hosts are less likely to be hosted by quiescent galaxies, but more likely to be hosted by Main Sequence or starburst galaxies.

To achieve faster and equitable improvements in maternal and child health outcomes, the government of India launched the National Rural Health Mission in 2005. This paper describes the equity-enhancing role of the public sector in increasing use of institutional delivery care services in India between 2004 and 2014. Information on 24 661 births from nationally representative survey data for 2004 and 2014 is analysed. Concentration index is computed to describe socioeconomic-rank-related relative inequalities in institutional delivery and decomposition is used to assess the contributions of public and private sectors in overall socioeconomic inequality. Multilevel logistic regression is applied to examine the changes in socioeconomic gradient between 2004 and 2014. The analysis finds that utilization of institutional delivery care in India increased from 43% in 2004 to 83% in 2014. The bulk of the increase was in public sector use (21% in 2004 to 53% in 2014) with a modest increase in private sector use (22% in 2004 to 30% in 2014). The shift from a pro-rich to pro-poor distribution of public sector use is confirmed. Decomposition analysis indicates that 51% of these reductions in socioeconomic inequality are associated with improved pro-poor distribution of public sector births. Multilevel logistic regressions confirm the disappearance of a wealth-based gradient in public sector births between 2004 and 2014. We conclude that public health investments in India have significantly contributed towards an equitable increase in the coverage of institutional delivery care. Sustained policy efforts are necessary, however, with an emphasis on education, sociocultural and geographical factors to ensure universal coverage of institutional delivery care services in India.

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