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[Howie Daub] says: Well I'm glad Amish Randy spoke two sentences in this episode, which I believe brings his total for the season to about three. Mose is the only person you can actually believe is Amish. Mose also has an uncanny ability to talk like a robot. Anyway, could they have picked a more boring cast for the \"city\" kids? I am starting to believe city girl Ariel acts more Amish than most of the actual Amish kids. The only fitting sequel to this show would be moving city kids into Amish homes. But I guess Paris and Nicole already took that idea! There are religious reasons the Amish don't watch TV; then there are other reasons, like UPN. In this show, the Amish are interesting to watch and listen to, but the city kids are so irritating, they kill the momentum and turn the show into \"The Real World.\" I'm waiting for UPN to announce the sequel, \"Watch six posh L.A. 20- somethings turn up the heat on Antarctica!! Check your local listings!\"

Immunological health has been challenging to characterize but could be defined as the absence of immune pathology. While shared features of some immune diseases and the concept of immunologic resilience based on age-independent adaptation to antigenic stimulation have been developed, general metrics of immune health and its utility for assessing clinically healthy individuals remain ill defined. Here we integrated transcriptomics, serum protein, peripheral immune cell frequency and clinical data from 228 patients with 22 monogenic conditions impacting key immunological pathways together with 42 age- and sex-matched healthy controls. Despite the high penetrance of monogenic lesions, differences between individuals in diverse immune parameters tended to dominate over those attributable to disease conditions or medication use. Unsupervised or supervised machine learning independently identified a score that distinguished healthy participants from patients with monogenic diseases, thus suggesting a quantitative immune health metric (IHM). In ten independent datasets, the IHM discriminated healthy from polygenic autoimmune and inflammatory disease states, marked aging in clinically healthy individuals, tracked disease activities and treatment responses in both immunological and nonimmunological diseases, and predicted age-dependent antibody responses to immunizations with different vaccines. This discriminatory power goes beyond that of the classical inflammatory biomarkers C-reactive protein and interleukin-6. Thus, deviations from health in diverse conditions, including aging, have shared systemic immune consequences, and we provide a web platform for calculating the IHM for other datasets, which could empower precision medicine. A multimodal analysis of patients with 22 different immune-mediated monogenic diseases versus matched healthy controls leads to the development of the immune health metric, which could be implemented broadly to predict responses to aging, vaccination and other immune perturbations.