instruction:
In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.
question:
Estimating temporal changes in a target population from phylogenetic or count data is an important problem in ecology and epidemiology. Reliable estimates can provide key insights into the climatic and biological drivers influencing the diversity or structure of that population and evidence hypotheses concerning its future growth or decline. In infectious disease applications, the individuals infected across an epidemic form the target population. The renewal model estimates the effective reproduction number, R, of the epidemic from counts of its observed cases. The skyline model infers the effective population size, N, underlying a phylogeny of sequences sampled from that epidemic. Practically, R measures ongoing epidemic growth while N informs on historical caseload. While both models solve distinct problems, the reliability of their estimates depends on p-dimensional piecewise-constant functions. If p is misspecified, the model might underfit significant changes or overfit noise and promote a spurious understanding of the epidemic, which might misguide intervention policies or misinform forecasts. Surprisingly, no transparent yet principled approach for optimising p exists. Usually, p is heuristically set, or obscurely controlled via complex algorithms. We present a computable and interpretable p-selection method based on the minimum description length (MDL) formalism of information theory. Unlike many standard model selection techniques, MDL accounts for the additional statistical complexity induced by how parameters interact. As a result, our method optimises p so that R and N estimates properly adapt to the available data. It also outperforms comparable Akaike and Bayesian information criteria on several classification problems. Our approach requires some knowledge of the parameter space and exposes the similarities between renewal and skyline models.
answer:
Adaptive Estimation for Epidemic Renewal and Phylogenetic Skyline Models

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This paper combines two advances to detect MERS-CoV, the causative agent of Middle East Respiratory Syndrome, that have emerged over the past few years from the new field of "synthetic biology". Both are based on an older concept, where molecular beacons are used as the downstream detection of viral RNA in biological mixtures followed by reverse transcription PCR amplification. The first advance exploits the artificially expanded genetic information systems (AEGIS). AEGIS adds nucleotides to the four found in standard DNA and RNA (xNA); AEGIS nucleotides pair orthogonally to the A:T and G:C pairs. Placing AEGIS components in the stems of molecular beacons is shown to lower noise by preventing unwanted stem invasion by adventitious natural xNA. This should improve the signal-to-noise ratio of molecular beacons operating in complex biological mixtures. The second advance introduces a nicking enzyme that allows a single target molecule to activate more than one beacon, allowing "signal amplification". Combining these technologies in primers with components of a self-avoiding molecular recognition system (SAMRS), we detect 50 copies of MERS-CoV RNA in a multiplexed respiratory virus panel by generating fluorescence signal visible to human eye and/or camera.
answer:
Standard and AEGIS nicking molecular beacons detect amplicons from the Middle East respiratory syndrome coronavirus

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Four out of five people in the world with diabetes now live in low-and middle-income countries (LMIC), and the incidence of diabetes is accelerating in poorer communities. Diabetes increases susceptibility to infection and worsens outcomes for some of the world's major infectious diseases such as tuberculosis, melioidosis and dengue, but the relationship between diabetes and many neglected tropical diseases is yet to be accurately characterised. There is some evidence that chronic viral infections such as hepatitis B and HIV may predispose to the development of type 2 diabetes by chronic inflammatory and immunometabolic mechanisms. Helminth infections such as schistosomiasis may be protective against the development of diabetes, and this finding opens up new territory for discovery of novel therapeutics for the prevention and treatment of diabetes. A greater understanding of the impact of diabetes on risks and outcomes for infections causing significant diseases in LMIC is essential in order to develop vaccines and therapies for the growing number of people with diabetes at risk of infection, and to prioritise research agendas, public health interventions and policy. This review seeks to give an overview of the current international diabetes burden, the evidence for interactions between diabetes and infection, immune mechanisms for the interaction, and potential interventions to tackle the dual burden of diabetes and infection.
answer:
The double burden of diabetes and global infection in low and middle- income countries