Quantifying resilience of humans and other animals

All life requires the capacity to recover from challenges that are as inevitable as they are unpredictable. Understanding this resilience is essential for managing the health of humans and their livestock. It has long been difficult to quantify resilience directly, forcing practitioners to rely on indirect static indicators of health. However, measurements from wearable electronics and other sources now allow us to analyze the dynamics of physiology and behavior with unsurpassed resolution. The resulting flood of data coincides with the emergence of novel analytical tools for estimating resilience from the pattern of micro-recoveries observed in natural time series. Such dynamic indicators of resilience (DIORs) may be used to monitor the risk of systemic failure across systems ranging from organs to entire organisms. These tools invite a fundamental rethink of our approach to the adaptive management of health and resilience

Health and Disease—Emergent States Resulting From Adaptive Social and Biological Network Interactions

Health is an adaptive state unique to each person. This subjective state must be distinguished from the objective state of disease. The experience of health and illness (or poor health) can occur both in the absence and presence of objective disease. Given that the subjective experience of health, as well as the finding of objective disease in the community, follow a Pareto distribution, the following questions arise: What are the processes that allow the emergence of four observable states—(1) subjective health in the absence of objective disease, (2) subjective health in the presence of objective disease, (3) illness in the absence of objective disease, and (4) illness in the presence of objective disease? If we consider each individual as a unique biological system, these four health states must emerge from physiological network structures and personal behaviors. The underlying physiological mechanisms primarily arise from the dynamics of external environmental and internal patho/physiological stimuli, which activate regulatory systems including the hypothalamic-pituitary-adrenal axis and autonomic nervous system. Together with other systems, they enable feedback interactions between all of the person's system domains and impact on his system's entropy. These interactions affect individual behaviors, emotional, and cognitive responses, as well as molecular, cellular, and organ system level functions. This paper explores the hypothesis that health is an emergent state that arises from hierarchical network interactions between a person's external environment and internal physiology. As a result, the concept of health synthesizes available qualitative and quantitative evidence of interdependencies and constraints that indicate its top-down and bottom-up causative mechanisms. Thus, to provide effective care, we must use strategies that combine person-centeredness with the scientific approaches that address the molecular network physiology, which together underpin health and disease. Moreover, we propose that good health can also be promoted by strengthening resilience and self-efficacy at the personal and social level, and via cohesion at the population level. Understanding health as a state that is both individualized and that emerges from multi-scale interdependencies between microlevel physiological mechanisms of health and disease and macrolevel societal domains may provide the basis for a new public discourse for health service and health system redesign

Measurement of dynamical resilience indicators improves the prediction of recovery following hospitalization in older adults

\u3cp\u3eOBJECTIVES: Acute illnesses and subsequent hospital admissions present large health stressors to older adults, after which their recovery is variable. The concept of physical resilience offers opportunities to develop dynamical tools to predict an individual's recovery potential. This study aimed to investigate if dynamical resilience indicators based on repeated physical and mental measurements in acutely hospitalized geriatric patients have added value over single baseline measurements in predicting favorable recovery.\u3c/p\u3e\u3cp\u3eDESIGN: Intensive longitudinal study.\u3c/p\u3e\u3cp\u3eSETTING AND PARTICIPANTS: 121 patients (aged 84.3 ± 6.2 years, 60% female) admitted to the geriatric ward for acute illness.\u3c/p\u3e\u3cp\u3eMEASUREMENTS: In addition to preadmission characteristics (frailty, multimorbidity), in-hospital heart rate and physical activity were continuously monitored with a wearable sensor. Momentary well-being (life satisfaction, anxiety, discomfort) was measured by experience sampling 4 times per day. The added value of dynamical indicators of resilience was investigated for predicting recovery at hospital discharge and 3 months later.\u3c/p\u3e\u3cp\u3eRESULTS: 31% of participants satisfied the criteria of good recovery at hospital discharge and 50% after 3 months. A combination of a frailty index, multimorbidity, Clinical Frailty Scale, and or gait speed predicted good recovery reasonably well on the short term [area under the receiver operating characteristic curve (AUC) = 0.79], but only moderately after 3 months (AUC = 0.70). On addition of dynamical resilience indicators, the AUC for predicting good 3-month recovery increased to 0.79 (P = .03). Variability in life satisfaction and anxiety during the hospital stay were independent predictors of good 3-month recovery [odds ratio (OR) = 0.24, P = .01, and OR = 0.54, P = .04, respectively].\u3c/p\u3e\u3cp\u3eCONCLUSIONS AND IMPLICATIONS: These results highlight that measurements capturing the dynamic functioning of multiple physiological systems have added value in assessing physical resilience in clinical practice, especially those monitoring mental responses. Improved monitoring and prediction of physical resilience could help target intensive treatment options and subsequent geriatric rehabilitation to patients who will most likely benefit from them.\u3c/p\u3

Adipocytes harbor a glucosylceramide biosynthesis pathway involved in iNKT cell activation

Background: Natural killer T (NKT)cells in adipose tissue (AT)contribute to whole body energy homeostasis. Results: Inhibition of the glucosylceramide synthesis in adipocytes impairs iNKT cell activity. Conclusion: Glucosylceramide biosynthesis pathway is important for endogenous lipid antigen activation of iNKT cells in adipocytes. Significance: Unraveling adipocyte-iNKT cell communication may help to fight obesity-induced AT dysfunction. Overproduction and/or accumulation of ceramide and ceramide metabolites, including glucosylceramides, can lead to insulin resistance. However, glucosylceramides also fulfill important physiological functions. They are presented by antigen presenting cells (APC)as endogenous lipid antigens via CD1d to activate a unique lymphocyte subspecies, the CD1d-restricted invariant (i)natural killer T (NKT)cells. Recently, adipocytes have emerged as lipid APC that can activate adipose tissue-resident iNKT cells and thereby contribute to whole body energy homeostasis. Here we investigate the role of the glucosylceramide biosynthesis pathway in the activation of iNKT cells by adipocytes. UDP-glucose ceramide glucosyltransferase (Ugcg), the first rate limiting step in the glucosylceramide biosynthesis pathway, was inhibited via chemical compounds and shRNA knockdown in vivo and in vitro. β-1,4-Galactosyltransferase (B4Galt)5 and 6, enzymes that convert glucosylceramides into potentially inactive lactosylceramides, were subjected to shRNA knock down. Subsequently, (pre)adipocyte cell lines were tested in co-culture experiments with iNKT cells (IFNγ and IL4 secretion). Inhibition of Ugcg activity shows that it regulates presentation of a considerable fraction of lipid self-antigens in adipocytes. Furthermore, reduced expression levels of either B4Galt5 or -6, indicate that B4Galt5 is dominant in the production of cellular lactosylceramides, but that inhibition of either enzyme results in increased iNKT cell activation. Additionally, in vivo inhibition of Ugcg by the aminosugar AMP-DNM results in decreased iNKT cell effector function in adipose tissue. Inhibition of endogenous glucosylceramide production results in decreased iNKT cells activity and cytokine production, underscoring the role of this biosynthetic pathway in lipid self-antigen presentation by adipocytes