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.

[EX Q]: | The ancient biological 'arms race' between microbial pathogens and humans has shaped genetic variation in modern populations, and this has important implications for the growing field of medical genomics. As humans migrated throughout the world, populations encountered distinct pathogens, and natural selection increased the prevalence of alleles that are advantageous in the new ecosystems in both host and pathogens. This ancient history now influences human infectious disease susceptibility and microbiome homeostasis, and contributes to common diseases that show geographical disparities, such as autoimmune and metabolic disorders. Using new high-throughput technologies, analytical methods and expanding public data resources, the investigation of natural selection is leading to new insights into the function and dysfunction of human biology. www.nature.com/reviews/genetics
[EX A]: Natural selection and infectious disease in human populations

[EX Q]: Contact networks are convenient models to investigate epidemics, with nodes and links representing potential hosts and infection pathways, respectively. The outcomes of outbreak simulations on networks are driven both by the underlying epidemic model, and by the networks' structural properties, so that the same pathogen can generate different epidemic dynamics on different networks. Here we ask whether there are general properties that make a contact network intrinsically vulnerable to epidemics (that is, regardless of specific epidemiological parameters). By conducting simulations on a large set of modelled networks, we show that, when a broad range of network topologies is taken into account, the effect of specific network properties on outbreak magnitude is stronger than that of fundamental pathogen features such as transmission rate, infection duration, and immunization ability. Then, by focusing on a large set of real world networks of the same type (potential contacts between field voles, Microtus agrestis), we showed how network structure can be used to accurately assess the relative, intrinsic vulnerability of networks towards a specific pathogen, even when those have limited topological variability. These results have profound implications for how we prevent disease outbreaks; in many real world situations, the topology of host contact networks can be described and used to infer intrinsic vulnerability. Such an approach can increase preparedness and inform preventive measures against emerging diseases for which limited epidemiological information is available, enabling the identification of priority targets before an epidemic event.
[EX A]: The intrinsic vulnerability of networks to epidemics

[EX Q]: This commentary represents a selective survey of developments relevant to critical care. Selected themes include advances in point-of-care diagnostic testing, glucose control, novel microbiological diagnostics and infection control measures, and developments in information technology that have implications for intensive care. The latter encompasses an early example of an artificially intelligent clinical decision support mechanism, the introduction of a national health care information technology programme (UK NPfIT) and its implications, and exotic threats to patient safety due to emergent behaviour in complex information systems. Keywords glucose, health technology assessment, information technology, intensive care, point-of-care US Food and Drug Administration (FDA) http://www.fda.gov/ UK Medicines and Healthcare Products Regulatory Agency (MHRA)
[EX A]:
Canadian Coordinating Office for Health Technology Assessment (CCOHTA)