Bayesian hierarchical modelling approaches for combining information from multiple data sources to produce annual estimates of national immunization coverage

Estimates of national immunization coverage are crucial for guiding policy and decision-making in national immunization programs and setting the global immunization agenda. WHO and UNICEF estimates of national immunization coverage (WUENIC) are produced annually for various vaccine-dose combinations and all WHO Member States using information from multiple data sources and a deterministic computational logic approach. This approach, however, is incapable of characterizing the uncertainties inherent in coverage measurement and estimation. It also provides no statistically principled way of exploiting and accounting for the interdependence in immunization coverage data collected for multiple vaccines, countries and time points. Here, we develop Bayesian hierarchical modeling approaches for producing accurate estimates of national immunization coverage and their associated uncertainties. We propose and explore two candidate models: a balanced data single likelihood (BDSL) model and an irregular data multiple likelihood (IDML) model, both of which differ in their handling of missing data and characterization of the uncertainties associated with the multiple input data sources. We provide a simulation study that demonstrates a high degree of accuracy of the estimates produced by the proposed models, and which also shows that the IDML model is the better model. We apply the methodology to produce coverage estimates for select vaccine-dose combinations for the period 2000-2019. A contributed R package {\tt imcover} implementing the No-U-Turn Sampler (NUTS) in the Stan programming language enhances the utility and reproducibility of the methodology.Comment: 31 pages (main), 4 figure

The Power of 3 Collaborative creation of an Irish online, open access, digital humanities research resource to support professional training in archives management.

This poster describes a 3U Partnership Humanities collaboration involving the Department of History at Maynooth University and the libraries in each of the three partner institutions. the aim was to build upon on a joint archives digitisation project that incorporated significant interpretation of the archival content. It involved a sharing of expertise in digitisation, system building, academic connections and a broader humanities project than any institution could achieve alone

Itaconate is an anti-inflammatory metabolite that activates Nrf2 via alkylation of KEAP1.

The endogenous metabolite itaconate has recently emerged as a regulator of macrophage function, but its precise mechanism of action remains poorly understood. Here we show that itaconate is required for the activation of the anti-inflammatory transcription factor Nrf2 (also known as NFE2L2) by lipopolysaccharide in mouse and human macrophages. We find that itaconate directly modifies proteins via alkylation of cysteine residues. Itaconate alkylates cysteine residues 151, 257, 288, 273 and 297 on the protein KEAP1, enabling Nrf2 to increase the expression of downstream genes with anti-oxidant and anti-inflammatory capacities. The activation of Nrf2 is required for the anti-inflammatory action of itaconate. We describe the use of a new cell-permeable itaconate derivative, 4-octyl itaconate, which is protective against lipopolysaccharide-induced lethality in vivo and decreases cytokine production. We show that type I interferons boost the expression of Irg1 (also known as Acod1) and itaconate production. Furthermore, we find that itaconate production limits the type I interferon response, indicating a negative feedback loop that involves interferons and itaconate. Our findings demonstrate that itaconate is a crucial anti-inflammatory metabolite that acts via Nrf2 to limit inflammation and modulate type I interferons

Use and limitations of quick tests in antibiotic residue testing in milk

In summary, this research topic aimed to describe why and how antibiotic residues in milk are strictly controlled in the dairy industry. A number of quick tests including the Delvotest, the Snaptest and the brilliant black reduction test have been developed to allow farmers and creameries to monitor the levels of antibiotics in milk. The thesis also aimed to investigate the sensitivities of the Delvotest to two drugs and if cleaning products could give false results for the test

The Power of 3 Collaborative creation of an Irish online, open access, digital humanities research resource to support professional training in archives management.

This poster describes a 3U Partnership Humanities collaboration involving the Department of History at Maynooth University and the libraries in each of the three partner institutions. the aim was to build upon on a joint archives digitisation project that incorporated significant interpretation of the archival content. It involved a sharing of expertise in digitisation, system building, academic connections and a broader humanities project than any institution could achieve alone