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 microrecoveries observed in natural time series. Such dynamic indicators of resilience may be used to monitor the risk of systemic failure across systems ranging from organs to entire organisms. These tools invite a fundamental rethinking of our approach to the adaptive management of health and resilience.

CD1d-mediated presentation of endogenous lipid antigens by adipocytes requires microsomal triglyceride transfer protein.

Obesity-induced adipose tissue (AT) dysfunction results in a chronic low-grade inflammation that predisposes to the development of insulin resistance and type 2 diabetes. During the development of obesity, the AT-resident immune cell profile alters to create a pro-inflammatory state. Very recently, CD1d-restricted invariant (i) natural killer T (NKT) cells, a unique subset of lymphocytes that are reactive to so called lipid antigens, were implicated in AT homeostasis. Interestingly, recent data also suggest that human and mouse adipocytes can present such lipid antigens to iNKT cells in a CD1d-dependent fashion, but little is known about the lipid antigen presentation machinery in adipocytes. Here we show that CD1d, as well as the lipid antigen loading machinery genes pro-saposin (Psap), Niemann Pick type C2 (Npc2), α-galactosidase (Gla), are up-regulated in early adipogenesis, and are transcriptionally controlled by CCAAT/enhancer-binding protein (C/EBP)-ß and -δ. Moreover, adipocyte-induced Th1 and Th2 cytokine release by iNKT cells also occurred in the absence of exogenous ligands, suggesting the display of endogenous lipid antigen-D1d complexes by 3T3-L1 adipocytes. Furthermore, we identified microsomal triglyceride transfer protein, which we show is also under the transcriptional regulation of C/EBPß and -δ, as a novel player in the presentation of endogenous lipid antigens by adipocytes. Overall, our findings indicate that adipocytes can function as non-professional lipid antigen presenting cells, which may present an important aspect of adipocyte-immune cell communication in the regulation of whole body energy metabolism and immune homeostasis.

Dynamical indicators of resilience from physiological time series in geriatric inpatients: Lessons learned.

The concept of physical resilience may help geriatric medicine objectively assess patients' ability to 'bounce back' from future health challenges. Indicators putatively forecasting resilience have been developed under two paradigms with different perspectives: Critical Slowing Down and Loss of Complexity. This study explored whether these indicators validly reflect the construct of resilience in geriatric inpatients. Geriatric patients (n = 121, 60% female) had their heart rate and physical activity continuously monitored using a chest-worn sensor. Indicators from both paradigms were extracted from both physiological signals. Measures of health functioning, concomitant with low resilience, were obtained by questionnaire at admission. The relationships among indicators and their associations with health functioning were assessed by correlation and linear regression analyses, respectively. Greater complexity and higher variance in physical activity were associated with lower frailty (ß = -0.28, p = .004 and ß = -0.37, p < .001, respectively) and better ADL function (ß = 0.23, p = .022 and ß = 0.38, p < .001). The associations of physical activity variance with health functioning were not in the expected direction based on Critical Slowing Down. In retrospect, these observations stress the importance of matching the resilience paradigm's assumptions to the homeostatic role of the variable monitored. We present several lessons learned.

Measurement of Dynamical Resilience Indicators Improves the Prediction of Recovery Following Hospitalization in Older Adults.

OBJECTIVES: 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. DESIGN: Intensive longitudinal study. SETTING AND PARTICIPANTS: 121 patients (aged 84.3 ± 6.2 years, 60% female) admitted to the geriatric ward for acute illness. MEASUREMENTS: 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. RESULTS: 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]. CONCLUSIONS 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.

Resilience in Clinical Care: Getting a Grip on the Recovery Potential of Older Adults.

BACKGROUND: Geriatricians are often confronted with unexpected health outcomes in older adults with complex multimorbidity. Aging researchers have recently called for a focus on physical resilience as a new approach to explaining such outcomes. Physical resilience, defined as the ability to resist functional decline or recover health following a stressor, is an emerging construct. METHODS: Based on an outline of the state-of-the-art in research on the measurement of physical resilience, this article describes what tests to predict resilience can already be used in clinical practice and which innovations are to be expected soon. RESULTS: An older adult's recovery potential is currently predicted by static tests of physiological reserves. Although geriatric medicine typically adopts a multidisciplinary view of the patient and implicitly performs resilience management to a certain extent, clinical management of older adults can benefit from explicitly applying the dynamical concept of resilience. Two crucial leads for advancing our capacity to measure and manage the resilience of individual patients are advocated: first, performing multiple repeated measurements around a stressor can provide insight about the patient's dynamic responses to stressors; and, second, linking psychological and physiological subsystems, as proposed by network studies on resilience, can provide insight into dynamic interactions involved in a resilient response. CONCLUSION: A big challenge still lies ahead in translating the dynamical concept of resilience into clinical tools and guidelines. As a first step in bridging this gap, this article outlines what opportunities clinicians and researchers can already exploit to improve prediction, understanding, and management of resilience of older adults. J Am Geriatr Soc 67:2650-2657, 2019.

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. ß-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.

Dynamical Indicators of Resilience in Postural Balance Time Series Are Related to Successful Aging in High-Functioning Older Adults.

BACKGROUND: Finding ways to quantify resilience as a predictor of a person's resistance to health challenges is important to improve healthy aging. This study investigated a unique sample of high-functioning older persons in whom traditional markers of frailty and functional decline are largely absent. Translating complex dynamical systems theory to humans, dynamical indicators of resilience in postural balance time series may sensitively discriminate levels of resilience. METHODS: This study investigated 240 high-functioning older adults (mean age 83.9 ± 2.9 years, 59% male), of whom 94 hikers of the Nijmegen Four Days Marches. Participants stood upright on a force plate with eyes open and feet at shoulder width for 30 seconds. Center of pressure data were analyzed for dynamical indicators of resilience (variance and temporal autocorrelation). After 1 year, participants were compared on a modified Successful Aging Index. RESULTS: Mediolateral center of pressure displacement of hikers exhibited significantly lower variance (2.2 vs 2.8 mm, p < .001) and temporal autocorrelation (0.59 vs 0.65, p = .006), compared with nonhikers. Multivariably adjusted, mediolateral variance was significantly associated with successful aging at baseline (b = -1.43, p = .003) and 1-year follow-up (b = -1.94, p < .001), while mediolateral temporal autocorrelation was not. CONCLUSIONS: Two dynamical indicators of resilience (variance and temporal autocorrelation) calculated on time series of mediolateral center of pressure displacement differed between hikers and nonhikers within a group of high-functioning older adults. In the whole group, variance was independently associated with successful aging at baseline and after 1 year. Our results support the hypothesis that resilience of older persons may be estimated from time series of natural fluctuations of bodily functions.

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.

Dynamical Resilience Indicators in Time Series of Self-Rated Health Correspond to Frailty Levels in Older Adults.

BACKGROUND: We currently still lack valid methods to dynamically measure resilience for stressors before the appearance of adverse health outcomes that hamper well-being. Quantifying an older adult's resilience in an early stage would aid complex decision-making in health care. Translating complex dynamical systems theory to humans, we hypothesized that three dynamical indicators of resilience (variance, temporal autocorrelation, and cross-correlation) in time series of self-rated physical, mental, and social health were associated with frailty levels in older adults. METHODS: We monitored self-rated physical, mental, and social health during 100 days using daily visual analogue scale questions in 22 institutionalized older adults (mean age 84.0, SD: 5.9 years). Frailty was determined by the Survey of Health, Ageing and Retirement in Europe (SHARE) frailty index. The resilience indicators (variance, temporal autocorrelation, and cross-correlation) were calculated using multilevel models. RESULTS: The self-rated health time series of frail elderly exhibited significantly elevated variance in the physical, mental, and social domain, as well as significantly stronger cross-correlations between all three domains, as compared to the nonfrail group (all P < 0.001). Temporal autocorrelation was not significantly associated with frailty. CONCLUSIONS: We found supporting evidence for two out of three hypothesized resilience indicators to be related to frailty levels in older adults. By mirroring the dynamical resilience indicators to a frailty index, we delivered a first empirical base to validate and quantify the construct of systemic resilience in older adults in a dynamic way.