Potential long consequences from internal and external ecology: loss of gut microbiota antifragility in children from an industrialized population compared with an indigenous rural lifestyle

Human health is strongly mediated by the gut microbiota ecosystem, which, in turn, depends not only on its state but also on its dynamics and how it responds to perturbations. Healthy microbiota ecosystems tend to be in criticality and antifragile dynamics corresponding to a maximum complexity configuration, which may be assessed with information and network theory analysis. Under this complex system perspective, we used a new analysis of published data to show that a children's population with an industrialized urban lifestyle from Mexico City exhibits informational and network characteristics similar to parasitized children from a rural indigenous population in the remote mountainous region of Guerrero, México. We propose then, that in this critical age for gut microbiota maturation, the industrialized urban lifestyle could be thought of as an external perturbation to the gut microbiota ecosystem, and we show that it produces a similar loss in criticality/antifragility as the one observed by internal perturbation due to parasitosis by the helminth A. lumbricoides. Finally, several general complexity-based guidelines to prevent or restore gut ecosystem antifragility are discussed.

Health Service Implementation and Antifragile Characteristics in Rural Communities: A Dirt Research Approach

The implementation of health and care services within rural communities requires necessary sensitivity to the unique facets of rural places. Often, rural service implementation is executed with inappropriate frameworks based on assumptions derived from urban centres. To understand the characteristics of rural communities that can facilitate successful program implementation better, ethnographic accounts of rural health and care services were compiled in rural communities within Canada, Australia, and Iceland. Ethnographic accounts are presented in the first and third person, with an accompanying reflexive analysis immediately following these accounts. Antifragility was the guiding concept of interest when investigating rural implementation environments, a concept that posits that a system can gain stability from uncertainty rather than lose integrity. These ethnographic accounts provide evidence of antifragile operators such as optionality, hybrid leadership, starting small, nonlinear evaluation, and avoiding suboptimisation. It is shown that the integration of these antifragile operators allows programs to function better in complex rural systems. Further, the presence of capable individuals with sufficient knowledge in several disciplines and with depth in a single discipline allows for innovative local thinking initiatives.

Brindley's Glands Volatilome of the Predator Zelus renardii Interacting with Xylella Vectors

Alien species must adapt to new biogeographical regions to acclimatise and survive. We consider a species to have become invasive if it establishes negative interactions after acclimatisation. Xylella fastidiosa Wells, Raju et al., 1986 (XF) represents Italy's and Europe's most recent biological invasion. In Apulia (southern Italy), the XF-encountered Philaenus spumarius L. 1758 (Spittlebugs, Hemiptera: Auchenorrhyncha) can acquire and transmit the bacterium to Olea europaea L., 1753. The management of XF invasion involves various transmission control means, including inundative biological control using Zelus renardii (ZR) Kolenati, 1856 (Hemiptera: Reduviidae). ZR is an alien stenophagous predator of Xylella vectors, recently entered from the Nearctic and acclimated in Europe. Zelus spp. can secrete semiochemicals during interactions with conspecifics and prey, including volatile organic compounds (VOCs) that elicit conspecific defence behavioural responses. Our study describes ZR Brindley's glands, present in males and females of ZR, which can produce semiochemicals, eliciting conspecific behavioural responses. We scrutinised ZR secretion alone or interacting with P. spumarius. The ZR volatilome includes 2-methyl-propanoic acid, 2-methyl-butanoic acid, and 3-methyl-1-butanol, which are consistent for Z. renardii alone. Olfactometric tests show that these three VOCs, individually tested, generate an avoidance (alarm) response in Z. renardii. 3-Methyl-1-butanol elicited the highest significant repellence, followed by 2-methyl-butanoic and 2-methyl-propanoic acids. The concentrations of the VOCs of ZR decrease during the interaction with P. spumarius. We discuss the potential effects of VOC secretions on the interaction of Z. renardii with P. spumarius.

Toward Antifragility: Social Defeat Stress Enhances Learning and Memory in Young Mice Via Hippocampal Synaptosome Associated Protein 25

Social adversity not only causes severe psychological diseases but also may improve people's ability to learn and grow. However, the beneficial effects of social adversity are often ignored. In this study, we investigated whether and how social adversity affects learning and memory in a mouse social defeat stress (SDS) model. A total of 652 mice were placed in experimental groups of six to 23 mice each. SDS enhanced spatial, novelty, and fear memory with increased synaptosome associated protein 25 (SNAP-25) level and dendritic spine density in hippocampal neurons among young but not middle-aged mice. Chemogenetic inhibition of hippocampal CaMK2A+ neurons blocked SDS-induced enhancement of learning or memory. Knockdown of SNAP-25 or blockade of N-methyl-D-aspartate (NMDA) receptor subunit GluN2B in the hippocampus prevented SDS-induced learning memory enhancement in an emotion-independent manner. These findings suggest that social adversity promotes learning and memory ability in youths and provide a neurobiological foundation for biopsychological antifragility.

Working with Convex Responses: Antifragility from Finance to Oncology

We extend techniques and learnings about the stochastic properties of nonlinear responses from finance to medicine, particularly oncology, where it can inform dosing and intervention. We define antifragility. We propose uses of risk analysis for medical problems, through the properties of nonlinear responses (convex or concave). We (1) link the convexity/concavity of the dose-response function to the statistical properties of the results; (2) define "antifragility" as a mathematical property for local beneficial convex responses and the generalization of "fragility" as its opposite, locally concave in the tails of the statistical distribution; (3) propose mathematically tractable relations between dosage, severity of conditions, and iatrogenics. In short, we propose a framework to integrate the necessary consequences of nonlinearities in evidence-based oncology and more general clinical risk management.

"Ectomosphere": Insects and Microorganism Interactions

This study focuses on interacting with insects and their ectosymbiont (lato sensu) microorganisms for environmentally safe plant production and protection. Some cases help compare ectosymbiont microorganisms that are insect-borne, -driven, or -spread relevant to endosymbionts' behaviour. Ectosymbiotic bacteria can interact with insects by allowing them to improve the value of their pabula. In addition, some bacteria are essential for creating ecological niches that can host the development of pests. Insect-borne plant pathogens include bacteria, viruses, and fungi. These pathogens interact with their vectors to enhance reciprocal fitness. Knowing vector-phoront interaction could considerably increase chances for outbreak management, notably when sustained by quarantine vector ectosymbiont pathogens, such as the actual Xylella fastidiosa Mediterranean invasion episode. Insect pathogenic viruses have a close evolutionary relationship with their hosts, also being highly specific and obligate parasites. Sixteen virus families have been reported to infect insects and may be involved in the biological control of specific pests, including some economic weevils. Insects and fungi are among the most widespread organisms in nature and interact with each other, establishing symbiotic relationships ranging from mutualism to antagonism. The associations can influence the extent to which interacting organisms can exert their effects on plants and the proper management practices. Sustainable pest management also relies on entomopathogenic fungi; research on these species starts from their isolation from insect carcasses, followed by identification using conventional light or electron microscopy techniques. Thanks to the development of omics sciences, it is possible to identify entomopathogenic fungi with evolutionary histories that are less-shared with the target insect and can be proposed as pest antagonists. Many interesting omics can help detect the presence of entomopathogens in different natural matrices, such as soil or plants. The same techniques will help localize ectosymbionts, localization of recesses, or specialized morphological adaptation, greatly supporting the robust interpretation of the symbiont role. The manipulation and modulation of ectosymbionts could be a more promising way to counteract pests and borne pathogens, mitigating the impact of formulates and reducing food insecurity due to the lesser impact of direct damage and diseases. The promise has a preventive intent for more manageable and broader implications for pests, comparing what we can obtain using simpler, less-specific techniques and a less comprehensive approach to Integrated Pest Management (IPM).

Temporal, Structural, and Functional Heterogeneities Extend Criticality and Antifragility in Random Boolean Networks

Most models of complex systems have been homogeneous, i.e., all elements have the same properties (spatial, temporal, structural, functional). However, most natural systems are heterogeneous: few elements are more relevant, larger, stronger, or faster than others. In homogeneous systems, criticality-a balance between change and stability, order and chaos-is usually found for a very narrow region in the parameter space, close to a phase transition. Using random Boolean networks-a general model of discrete dynamical systems-we show that heterogeneity-in time, structure, and function-can broaden additively the parameter region where criticality is found. Moreover, parameter regions where antifragility is found are also increased with heterogeneity. However, maximum antifragility is found for particular parameters in homogeneous networks. Our work suggests that the "optimal" balance between homogeneity and heterogeneity is non-trivial, context-dependent, and in some cases, dynamic.

Research, kindness and the antifragility of emergency medicine

Antifragility is a property of things that benefit from shocks, randomness and uncertainty and love adventure and risk. This describes emergency medicine. Improving evidence-based medicine requires a learning health system, where the whole system is constructed to advance patient care via research driven excellence. So we need to develop our own evidence base by embedding research into everyday practice. Clinical research is messy but the repeated stress testing of clinical practice via research enhances our antifragility. This is even more important because our world is complex, as are humans. Unfortunately, the human brain is hard wired for simplicity, making us disinclined to challenge the status quo. Yet probably <10% of our practice is supported by high-level evidence. Research is altruistic and a form of kindness for our patients, which includes having a culture of research within a learning health system, so that we can be thoughtful!

Guiding the Self-Organization of Cyber-Physical Systems

Self-organization offers a promising approach for designing adaptive systems. Given the inherent complexity of most cyber-physical systems, adaptivity is desired, as predictability is limited. Here I summarize different concepts and approaches that can facilitate self-organization in cyber-physical systems, and thus be exploited for design. Then I mention real-world examples of systems where self-organization has managed to provide solutions that outperform classical approaches, in particular related to urban mobility. Finally, I identify when a centralized, distributed, or self-organizing control is more appropriate.

Towards an antifragile urban form: a research agenda for advancing resilience in the built environment

This paper aims to initiate reflections on what an antifragile (Taleb, Anti-fragile. Things that gain from disorder. Penguin Books, London 2012) built environment might look like by furthering the debate on dynamic non-equilibrium resilience, specifically in terms of scale, urban morphology and social life in urban areas. It will do so by presenting a critical review of relevant literature on resilience in the built environment and linking it to what we know so far about the physical (i.e. geographical, morphological and so on) and socio-cultural conditions that have likely limited the spread of COVID-19 while maintaining quality in urban space in early 2020. As the current pandemic is sharpening our understanding of both the link between local and global action and the power encompassed in the exercise of professional and technical knowledge and practice, the paper concludes with (i) speculations on how the current crisis and its management (i.e. lockdown and social distancing measures in public space’ use) might lead to radical changes to the way we think of, and design the conditions for, urban public life and sociability; and with (ii) an agenda for further research on what role urban forms and uses play in speeding or slowing viral spread in different contexts.

Antifragility Predicts the Robustness and Evolvability of Biological Networks through Multi-Class Classification with a Convolutional Neural Network

Robustness and evolvability are essential properties to the evolution of biological networks. To determine if a biological network is robust and/or evolvable, it is required to compare its functions before and after mutations. However, this sometimes takes a high computational cost as the network size grows. Here, we develop a predictive method to estimate the robustness and evolvability of biological networks without an explicit comparison of functions. We measure antifragility in Boolean network models of biological systems and use this as the predictor. Antifragility occurs when a system benefits from external perturbations. By means of the differences of antifragility between the original and mutated biological networks, we train a convolutional neural network (CNN) and test it to classify the properties of robustness and evolvability. We found that our CNN model successfully classified the properties. Thus, we conclude that our antifragility measure can be used as a predictor of the robustness and evolvability of biological networks.