Systems biology, emergence and antireductionism

A Network Toxicology Approach for Mechanistic Modelling of Nanomaterial Hazard and Adverse Outcomes

Hazard assessment is the first step in evaluating the potential adverse effects of chemicals. Traditionally, toxicological assessment has focused on the exposure, overlooking the impact of the exposed system on the observed toxicity. However, systems toxicology emphasizes how system properties significantly contribute to the observed response. Hence, systems theory states that interactions store more information than individual elements, leading to the adoption of network based models to represent complex systems in many fields of life sciences. Here, they develop a network-based approach to characterize toxicological responses in the context of a biological system, inferring biological system specific networks. They directly link molecular alterations to the adverse outcome pathway (AOP) framework, establishing direct connections between omics data and toxicologically relevant phenotypic events. They apply this framework to a dataset including 31 engineered nanomaterials with different physicochemical properties in two different in vitro and one in vivo models and demonstrate how the biological system is the driving force of the observed response. This work highlights the potential of network-based methods to significantly improve their understanding of toxicological mechanisms from a systems biology perspective and provides relevant considerations and future data-driven approaches for the hazard assessment of nanomaterials and other advanced materials.

Essential New Complexity-Based Themes for Patient-Centered Diagnosis and Treatment of Dementia and Predementia in Older People: Multimorbidity and Multilevel Phenomenology

Dementia is a highly prevalent condition with devastating clinical and socioeconomic sequela. It is expected to triple in prevalence by 2050. No treatment is currently known to be effective. Symptomatic late-onset dementia and predementia (SLODP) affects 95% of patients with the syndrome. In contrast to trials of pharmacological prevention, no treatment is suggested to remediate or cure these symptomatic patients. SLODP but not young onset dementia is intensely associated with multimorbidity (MUM), including brain-perturbating conditions (BPCs). Recent studies showed that MUM/BPCs have a major role in the pathogenesis of SLODP. Fortunately, most MUM/BPCs are medically treatable, and thus, their treatment may modify and improve SLODP, relieving suffering and reducing its clinical and socioeconomic threats. Regrettably, the complex system features of SLODP impede the diagnosis and treatment of the potentially remediable conditions (PRCs) associated with them, mainly due to failure of pattern recognition and a flawed diagnostic workup. We suggest incorporating two SLODP-specific conceptual themes into the diagnostic workup: MUM/BPC and multilevel phenomenological themes. By doing so, we were able to improve the diagnostic accuracy of SLODP components and optimize detecting and favorably treating PRCs. These revolutionary concepts and their implications for remediability and other parameters are discussed in the paper.

Systems Genome: Coordinated Gene Activity Networks, Recurring Coordination Modules, and Genome Homeostasis in Developing Neurons

As human progenitor cells differentiate into neurons, the activities of many genes change; these changes are maintained within a narrow range, referred to as genome homeostasis. This process, which alters the synchronization of the entire expressed genome, is distorted in neurodevelopmental diseases such as schizophrenia. The coordinated gene activity networks formed by altering sets of genes comprise recurring coordination modules, governed by the entropy-controlling action of nuclear FGFR1, known to be associated with DNA topology. These modules can be modeled as energy-transferring circuits, revealing that genome homeostasis is maintained by reducing oscillations (noise) in gene activity while allowing gene activity changes to be transmitted across networks; this occurs more readily in neuronal committed cells than in neural progenitors. These findings advance a model of an "entangled" global genome acting as a flexible, coordinated homeostatic system that responds to developmental signals, is governed by nuclear FGFR1, and is reprogrammed in disease.

Finding new analgesics: Computational pharmacology faces drug discovery challenges

Despite the worldwide prevalence and huge burden of pain, pain is an undertreated phenomenon. Currently used analgesics have several limitations regarding their efficacy and safety. The discovery of analgesics possessing a novel mechanism of action has faced multiple challenges, including a limited understanding of biological processes underpinning pain and analgesia and poor animal-to-human translation. Computational pharmacology is currently employed to face these challenges. In this review, we discuss the theory, methods, and applications of computational pharmacology in pain research. Computational pharmacology encompasses a wide variety of theoretical concepts and practical methodological approaches, with the overall aim of gaining biological insight through data acquisition and analysis. Data are acquired from patients or animal models with pain or analgesic treatment, at different levels of biological organization (molecular, cellular, physiological, and behavioral). Distinct methodological algorithms can then be used to analyze and integrate data. This helps to facilitate the identification of biological molecules and processes associated with pain phenotype, build quantitative models of pain signaling, and extract translatable features between humans and animals. However, computational pharmacology has several limitations, and its predictions can provide false positive and negative findings. Therefore, computational predictions are required to be validated experimentally before drawing solid conclusions. In this review, we discuss several case study examples of combining and integrating computational tools with experimental pain research tools to meet drug discovery challenges.

Redefining cancer research for therapeutic breakthroughs

Cancer research has played a pivotal role in improving patient outcomes. However, despite the significant investment in fundamental cancer research over the past few decades, the translation of funding into substantial advancements in cancer treatment has been limited. This perspective article employs a detailed analysis to outline strategies for promoting innovation and facilitating discoveries within the field of cancer research.

Molecular Insights into Transcranial Direct Current Stimulation Effects: Metabolomics and Transcriptomics Analyses

INTRODUCTION

Transcranial direct current stimulation (tDCS) is an evolving non-invasive neurostimulation technique. Despite multiple studies, its underlying molecular mechanisms are still unclear. Several previous human studies of the effect of tDCS suggest that it generates metabolic effects. The induction of metabolic effects by tDCS could provide an explanation for how it generates its long-term beneficial clinical outcome.

AIM

Given these hints of tDCS metabolic effects, we aimed to delineate the metabolic pathways involved in its mode of action.

METHODS

To accomplish this, we utilized a broad analytical approach of co-analyzing metabolomics and transcriptomic data generated from anodal tDCS in rat models. Since no metabolomic dataset was available, we performed a tDCS experiment of bilateral anodal stimulation of 200 µA for 20 min and for 5 consecutive days, followed by harvesting the brain tissue below the stimulating electrode and generating a metabolomics dataset using LC-MS/MS. The analysis of the transcriptomic dataset was based on a publicly available dataset.

RESULTS

Our analyses revealed that tDCS alters the metabolic profile of brain tissue, affecting bioenergetic-related pathways, such as glycolysis and mitochondrial functioning. In addition, we found changes in calcium-related signaling.

CONCLUSIONS

We conclude that tDCS affects metabolism by modulating energy production-related processes. Given our findings concerning calcium-related signaling, we suggest that the immediate effects of tDCS on calcium dynamics drive modifications in distinct metabolic pathways. A thorough understanding of the underlying molecular mechanisms of tDCS has the potential to revolutionize its applicability, enabling the generation of personalized medicine in the field of neurostimulation and thus contributing to its optimization.

Experimental platforms for functional genomics in ticks

Ticks are blood-feeding ectoparasites that devastate cattle farming and are an omnipresent nuisance to pets and humans, posing a threat of pathogen transmission. Laboratory experimental models can be instrumental in the search for molecular targets of novel acaricides or vaccines. Mainly, though, the experimental models represent invaluable tools for broadening our basic understanding of key processes of tick blood-feeding physiology and vector competence. In order to understand the function of a single component within the full complexity of a feeding tick, genetic or biochemical interventions are used for systemic phenotypisation. In this work, we summarise current experimental modalities that represent powerful approaches for determining biological functions of tick molecular components.

A unified method for assessing the observability of dynamic complex systems

PROBLEM

Systems theory applied to biology and medicine assumes that the complexity of a system can be described by quasi-generic models to predict the behavior of many other similar systems. To this end, the aim of various research works in systems theory is to develop inductive modeling (based on data-intensive analysis) or deductive modeling (based on the deduction of mechanistic principles) to discover patterns and identify plausible correlations between past and present events, or to connect different causal relationships of interacting elements at different scales and compute mathematical predictions. Mathematical principles assume that there are constant and observable universal causal principles that apply to all biological systems. Nowadays, there are no suitable tools to assess the soundness of these universal causal principles, especially considering that organisms not only respond to environmental stimuli (and inherent processes) across multiple scales but also integrate information about and within these scales. This implies an uncontrollable degree of uncertainty.

METHODOLOGY

A method has been developed to detect the stability of causal processes by evaluating the information contained in the trajectories identified in a phase space. Time series patterns are analyzed using concepts from geometric information theory and persistent homology. In essence, recognizing these patterns in different time periods and evaluating their geometrically integrated information leads to the assessment of causal relationships. With this method, and together with the evaluation of persistent entropy in trajectories in relation to different individual systems, we have developed a method called Φ-S diagram as a complexity measure to recognize when organisms follow causal pathways leading to mechanistic responses.

RESULTS

We calculated the Φ-S diagram of a deterministic dataset available in the ICU repository to test the method's interpretability. We also calculated the Φ-S diagram of time series from health data available in the same repository. This includes patients' physiological response to sport measured with wearables outside laboratory conditions. We confirmed the mechanistic nature of both datasets in both calculations. In addition, there is evidence that some individuals show a high degree of autonomous response and variability. Therefore, persistent individual variability may limit the ability to observe the cardiac response. In this study, we present the first demonstration of the concept of developing a more robust framework for representing complex biological systems.

Network medicine: an approach to complex kidney disease phenotypes

Scientific reductionism has been the basis of disease classification and understanding for more than a century. However, the reductionist approach of characterizing diseases from a limited set of clinical observations and laboratory evaluations has proven insufficient in the face of an exponential growth in data generated from transcriptomics, proteomics, metabolomics and deep phenotyping. A new systematic method is necessary to organize these datasets and build new definitions of what constitutes a disease that incorporates both biological and environmental factors to more precisely describe the ever-growing complexity of phenotypes and their underlying molecular determinants. Network medicine provides such a conceptual framework to bridge these vast quantities of data while providing an individualized understanding of disease. The modern application of network medicine principles is yielding new insights into the pathobiology of chronic kidney diseases and renovascular disorders by expanding the understanding of pathogenic mediators, novel biomarkers and new options for renal therapeutics. These efforts affirm network medicine as a robust paradigm for elucidating new advances in the diagnosis and treatment of kidney disorders.

Exosome Carrier Effects; Resistance to Digestion in Phagolysosomes May Assist Transfers to Targeted Cells; II Transfers of miRNAs Are Better Analyzed via Systems Approach as They Do Not Fit Conventional Reductionist Stoichiometric Concepts

Carrier effects of extracellular vesicles (EV) like exosomes refer to properties of the vesicles that contribute to the transferred biologic effects of their contents to targeted cells. This can pertain to ingested small amounts of xenogeneic plant miRNAs and oral administration of immunosuppressive exosomes. The exosomes contribute carrier effects on transfers of miRNAs by contributing both to the delivery and the subsequent functional intracellular outcomes. This is in contrast to current quantitative canonical rules that dictate just the minimum copies of a miRNA for functional effects, and thus successful transfers, independent of the EV carrier effects. Thus, we argue here that transfers by non-canonical minute quantities of miRNAs must consider the EV carrier effects of functional low levels of exosome transferred miRNA that may not fit conventional reductionist stoichiometric concepts. Accordingly, we have examined traditional stoichiometry vs. systems biology that may be more appropriate for delivered exosome functional responses. Exosome carrier properties discussed include; their required surface activating interactions with targeted cells, potential alternate targets beyond mRNAs, like reaching a threshold, three dimensional aspects of the RNAs, added EV kinetic dynamic aspects making transfers four dimensional, and unique intracellular release from EV that resist intracellular digestion in phagolysosomes. Together these EV carrier considerations might allow systems analysis. This can then result in a more appropriate understanding of transferred exosome carrier-assisted functional transfers. A plea is made that the miRNA expert community, in collaboration with exosome experts, perform new experiments on molecular and quantitative miRNA functional effects in systems that include EVs, like variation in EV type and surface constituents, delivery, dose and time to hopefully create more appropriate and truly current canonical concepts of the consequent miRNA functional transfers by EVs like exosomes.

George Orwell, objectivity, and the reality behind illusions

Illusions are commonly defined as departures of our percepts from the veridical representation of objective, common-sense reality. However, it has been claimed recently that this definition lacks validity, for example, on the grounds that external reality cannot possibly be represented truly by our sensory systems, and indeed may even be a fiction. Here, I first demonstrate how novelist George Orwell warned that such denials of objective reality are dangerous mistakes, in that they can lead to the suppression and even the atrophy of independent thought and critical evaluation. Second, anti-realists assume their opponents hold a fully reductionist metaphysics, in which fundamental physics describes the only ground truth, thereby placing it beyond direct human sensory observation. In contrast, I point to a more recent and commonly used alternative, non-reductive metaphysics. This ascribes real existence to many levels of dynamic systems of information, emerging progressively from the subatomic to the biological, psychological, social, and ecological. Within such a worldview the notion of objective reality is valid, it comes in part within the range of our senses, and thus a definition of illusions as kinds of deviations from veridical perception becomes possible again.

Multistability in Macrophage Activation Pathways and Metabolic Implications

Macrophages are innate immune cells with a dynamic range of reversible activation states including the classical pro-inflammatory (M1) and alternative anti-inflammatory (M2) states. Deciphering how macrophages regulate their transition from one state to the other is key for a deeper understanding of inflammatory diseases and relevant therapies. Common regulatory motifs reported for macrophage transitions, such as positive or double-negative feedback loops, exhibit a switchlike behavior, suggesting the bistability of the system. In this review, we explore the evidence for multistability (including bistability) in macrophage activation pathways at four molecular levels. First, a decision-making module in signal transduction includes mutual inhibitory interactions between M1 (STAT1, NF-KB/p50-p65) and M2 (STAT3, NF-KB/p50-p50) signaling pathways. Second, a switchlike behavior at the gene expression level includes complex network motifs of transcription factors and miRNAs. Third, these changes impact metabolic gene expression, leading to switches in energy production, NADPH and ROS production, TCA cycle functionality, biosynthesis, and nitrogen metabolism. Fourth, metabolic changes are monitored by metabolic sensors coupled to AMPK and mTOR activity to provide stability by maintaining signals promoting M1 or M2 activation. In conclusion, we identify bistability hubs as promising therapeutic targets for reverting or blocking macrophage transitions through modulation of the metabolic environment.

Multiscale Computational Modeling of Vascular Adaptation: A Systems Biology Approach Using Agent-Based Models

The widespread incidence of cardiovascular diseases and associated mortality and morbidity, along with the advent of powerful computational resources, have fostered an extensive research in computational modeling of vascular pathophysiology field and promoted in-silico models as a support for biomedical research. Given the multiscale nature of biological systems, the integration of phenomena at different spatial and temporal scales has emerged to be essential in capturing mechanobiological mechanisms underlying vascular adaptation processes. In this regard, agent-based models have demonstrated to successfully embed the systems biology principles and capture the emergent behavior of cellular systems under different pathophysiological conditions. Furthermore, through their modular structure, agent-based models are suitable to be integrated with continuum-based models within a multiscale framework that can link the molecular pathways to the cell and tissue levels. This can allow improving existing therapies and/or developing new therapeutic strategies. The present review examines the multiscale computational frameworks of vascular adaptation with an emphasis on the integration of agent-based approaches with continuum models to describe vascular pathophysiology in a systems biology perspective. The state-of-the-art highlights the current gaps and limitations in the field, thus shedding light on new areas to be explored that may become the future research focus. The inclusion of molecular intracellular pathways (e.g., genomics or proteomics) within the multiscale agent-based modeling frameworks will certainly provide a great contribution to the promising personalized medicine. Efforts will be also needed to address the challenges encountered for the verification, uncertainty quantification, calibration and validation of these multiscale frameworks.

Elimination of the toxic effect of copper sulfate is accompanied by the normalization of liver function in fibrosis

The search for biologically active compounds that regulate liver function in fibrosis is an urgent medical and biological problem. A working hypothesis was tested, according to which low molecular weight biologically active compounds from Pleurotus ostreatus and Sacharamirses cerevisiae are capable of exerting immunomodulatory and antitoxic effects after intoxication of the body with ions of heavy metals, in particular copper sulfate. Elimination of the toxic effect caused by copper sulfate can also ensure the normalization of liver function in various pathologies, in particular with liver fibrosis. When determining toxicity, a study was carried out on Wistar rats, and when studying the effect of low molecular weight biologically active compounds on liver function, clinical trials were carried out on volunteers. The activity of alanine aminotransferase, aspartate aminotransferase, actonitase and glutathione peroxidase, as well as the content of bilirubin and lipid hydroperoxides were determined. It was shown that preliminary administration of biologically active compounds to rats at a dose of 0.05 mL/100 g of body weight provided the formation in some animals (up to 80%) of resistance to the toxic effect of copper sulfate (dose 2.5 mg/100 g of body weight). Such stability is associated with a shift in the balance of “prooxidants-antioxidants” towards antioxidants. The data obtained in the clinic on volunteers with liver fibrosis and hepatitis also testify in favour of the membranotropic action of biologically active compounds. Biologically active compounds provided a decrease or complete restoration of the activity of transferases (ALT and AST) in the blood serum of these patients, with the exception of one patient out of 20 examined. Our experiment has shown the relationship between the elimination of toxicity to the action of copper sulfate and the normalization of liver function in patients. The results obtained indicate that it will be promising to use a complex of low molecular weight components from P. ostreatus and S. cerevisiae as an antidote and hepatoprotective agent.

Gene networks and microRNAs: Promises and challenges for treating epilepsies and their comorbidities

Neurobiology research has used an essentially reductionist approach for many years, dissecting out the brain in more simple elements. Recent technical advances, like systems biology, have made now possible to embrace a more holistic vision and try to tackle the complexity of the system. In this short review, we describe how these approaches, in particular analyses or gene networks and of microRNAs, may be useful for epilepsy research. We will describe and discuss recent studies that illustrate how these research approaches can lead to the identification of therapeutic targets and pharmacological strategies to prevent or treat some forms of epilepsy. We aim to show that studying epilepsy and its comorbidities within a complex system framework is a promising integration to the traditional reductionist approaches, and that it will become more and more important in the future for developing new therapies. This article is part of the Special Issue "NEWroscience 2018."

"Un-Promethean" science and the future of humanity: Heidegger's warning

The twentieth-century German philosopher Martin Heidegger distinguished "meditative" (besinnlich) and "calculative" (rechnende) modes of thinking as a way of highlighting the problematique of modern technology and the limits of modern science. In doing so he also was prescient to recognize, in 1955, that the most significant danger to the future of humanity are developments in molecular biology and biotechnology, in contrast to the post-World War global threat of thermonuclear weapons. These insights are engaged here in view of recent discussion of the need for international regulation of heritable human genome editing and the announcement in 2018 of the birth of the world's first gene-edited babies in China. Heidegger's call for meditative thinking requires modern medicine and the life sciences to appropriate the phenomenological conception of the human "way to be" (Seinsweise) such that it is not restricted to the "present-at-hand" (vorhanden) physiology and pathology of the human body (Körper).

Chaotic activation of developmental signalling pathways drives idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is characterised by an important remodelling of lung parenchyma. Current evidence indicates that the disease is triggered by alveolar epithelium activation following chronic lung injury, resulting in alveolar epithelial type 2 cell hyperplasia and bronchiolisation of alveoli. Signals are then delivered to fibroblasts that undergo differentiation into myofibroblasts. These changes in lung architecture require the activation of developmental pathways that are important regulators of cell transformation, growth and migration. Among others, aberrant expression of profibrotic Wnt-β-catenin, transforming growth factor-β and Sonic hedgehog pathways in IPF fibroblasts has been assessed. In the present review, we will discuss the transcriptional integration of these different pathways during IPF as compared with lung early ontogeny. We will challenge the hypothesis that aberrant transcriptional integration of these pathways might be under the control of a chaotic dynamic, meaning that a small change in baseline conditions could be sufficient to trigger fibrosis rather than repair in a chronically injured lung. Finally, we will discuss some potential opportunities for treatment, either by suppressing deleterious mechanisms or by enhancing the expression of pathways involved in lung repair. Whether developmental mechanisms are involved in repair processes induced by stem cell therapy will also be discussed.

miR-205: A Potential Biomedicine for Cancer Therapy

microRNAs (miRNAs) are a class of small non-coding RNAs that regulate the expression of their target mRNAs post transcriptionally. miRNAs are known to regulate not just a gene but the whole gene network (signaling pathways). Accumulating evidence(s) suggests that miRNAs can work either as oncogenes or tumor suppressors, but some miRNAs have a dual nature since they can act as both. miRNA 205 (miR-205) is one such highly conserved miRNA that can act as both, oncomiRNA and tumor suppressor. However, most reports confirm its emerging role as a tumor suppressor in many cancers. This review focuses on the downregulated expression of miR-205 and discusses its dysregulation in breast, prostate, skin, liver, gliomas, pancreatic, colorectal and renal cancers. This review also confers its role in tumor initiation, progression, cell proliferation, epithelial to mesenchymal transition, and tumor metastasis. Restoration of miR-205 makes cells more sensitive to drug treatments and mitigates drug resistance. Additionally, the importance of miR-205 in chemosensitization and its utilization as potential biomedicine and nanotherapy is described. Together, this review research article sheds a light on its application as a diagnostic and therapeutic marker, and as a biomedicine in cancer.

Vitalism in contemporary chiropractic: a help or a hinderance?

BACKGROUND

Chiropractic emerged in 1895 and was promoted as a viable health care substitute in direct competition with the medical profession. This was an era when there was a belief that one cause and one cure for all disease would be discovered. The chiropractic version was a theory that most diseases were caused by subluxated (slightly displaced) vertebrae interfering with "nerve vibrations" (a supernatural, vital force) and could be cured by adjusting (repositioning) vertebrae, thereby removing the interference with the body's inherent capacity to heal. DD Palmer, the originator of chiropractic, established chiropractic based on vitalistic principles. Anecdotally, the authors have observed that many chiropractors who overtly claim to be "vitalists" cannot define the term. Therefore, we sought the origins of vitalism and to examine its effects on chiropractic today.

DISCUSSION

Vitalism arose out of human curiosity around the biggest questions: Where do we come from? What is life? For some, life was derived from an unknown and unknowable vital force. For others, a vital force was a placeholder, a piece of knowledge not yet grasped but attainable. Developments in science have demonstrated there is no longer a need to invoke vitalistic entities as either explanations or hypotheses for biological phenomena. Nevertheless, vitalism remains within chiropractic. In this examination of vitalism within chiropractic we explore the history of vitalism, vitalism within chiropractic and whether a vitalistic ideology is compatible with the legal and ethical requirements for registered health care professionals such as chiropractors.

CONCLUSION

Vitalism has had many meanings throughout the centuries of recorded history. Though only vaguely defined by chiropractors, vitalism, as a representation of supernatural force and therefore an untestable hypothesis, sits at the heart of the divisions within chiropractic and acts as an impediment to chiropractic legitimacy, cultural authority and integration into mainstream health care.

Emergence and Evidence: A Close Look at Bunge’s Philosophy of Medicine

In his book “Medical Philosophy: Conceptual issues in Medicine”, Mario Bunge provides a unique account of medical philosophy that is deeply rooted in a realist ontology he calls “systemism”. According to systemism, the world consists of systems and their parts, and systems possess emergent properties that their parts lack. Events within systems may form causes and effects that are constantly conjoined via particular mechanisms. Bunge supports the views of the evidence-based medicine movement that randomized controlled trials (RCTs) provide the best evidence to establish the truth of causal hypothesis; in fact, he argues that only RCTs have this ability. Here, we argue that Bunge neglects the important feature of patients being open systems which are in steady interaction with their environment. We show that accepting this feature leads to counter-intuitive consequences for his account of medical hypothesis testing. In particular, we point out that (i) the confirmation of hypotheses is inherently stochastic and affords a probabilistic account of both confirmation and evidence which we provide here; (ii) RCTs are neither necessary nor sufficient to establish the truth of a causal claim; (iii) testing of causal hypotheses requires taking into account background knowledge and the context within which an intervention is applied. We conclude that there is no “best” research methodology in medicine, but that different methodologies should coexist in a complementary fashion.

Model Simulations Challenge Reductionist Research Approaches to Studying Chronic Low Back Pain

BACKGROUND

Traditionally, low back pain (LBP) is studied using a reductionist approach, in which the factors contributing to the clinical presentation of LBP are studied in isolation to identify the primary pathology or condition linked to LBP. We argue that reductionism may not be suitable for studying LBP, considering the complex, multifactorial nature of this condition.

OBJECTIVES

To quantify the likelihood of successfully subclassifying patients with LBP and effectively targeting treatment based on a single dominant factor contributing to LBP.

METHODS

Both analytical and numerical simulations (Monte Carlo) of 1 million patients with LBP were performed. Several factors contributing to LBP were randomly assigned to each individual. The following outcome measures were computed, as a function of the number of factors: the percentage of individuals who could be subclassified by identifying a single factor exceeding a certain threshold, and the average reduction in LBP when treatment eliminates the largest contributing factor versus a multimodal treatment that eliminates a number of the randomly selected factors.

RESULTS

With an increasing number of factors, the probability of subclassifying an individual to a subgroup based on a single factor tends toward zero. A multimodal treatment arbitrarily addressing any 2 or more factors was more effective than diagnosing and treating a single factor that maximally contributed to LBP.

CONCLUSION

Results suggest that reductionism is not appropriate for subclassifying patients with LBP or for targeting treatment. The use of reductionist approaches may explain some of the challenges when creating LBP classification systems and designing effective treatment interventions. J Orthop Sports Phys Ther 2019;49(6):477-481. Epub 15 May 2019. doi:10.2519/jospt.2019.8791.

Heterogeneity and emergent behaviour in the vascular endothelium

The endothelium is the single layer of cells lining all blood vessels, and it is a remarkable cardiovascular control centre. Each endothelial cell has only a small number (on average six) of interconnected neighbours. Yet this arrangement produces a large repertoire of behaviours, capable of controlling numerous cardiovascular functions in a flexible and dynamic way. The endothelium regulates the delivery of nutrients and removal of waste by regulating blood flow and vascular permeability. The endothelium regulates blood clotting, responses to infection and inflammation, the formation of new blood vessels, and remodelling of the blood vessel wall. To carry out these roles, the endothelium autonomously interprets a complex environment crammed with signals from hormones, neurotransmitters, pericytes, smooth muscle cells, various blood cells, viral or bacterial infection and proinflammatory cytokines. It is generally assumed that the endothelium responds to these instructions with coordinated responses in a homogeneous population of endothelial cells. Here, we highlight evidence that shows that neighbouring endothelial cells are highly heterogeneous and display different sensitivities to various activators. Cells with various sensitivities process different extracellular signals into distinct streams of information in parallel, like a vast switchboard. Communication occurs among cells and new ‘emergent’ signals are generated that are non-linear composites of the inputs. Emergent signals cannot be predicted or deduced from the properties of individual cells. Heterogeneity and emergent behaviour bestow capabilities on the endothelial collective that far exceed those of individual cells. The implications of heterogeneity and emergent behaviour for understanding vascular disease and drug discovery are discussed.

Cannabis and the Anxiety of Fragmentation-A Systems Approach for Finding an Anxiolytic Cannabis Chemotype

Cannabis sativa is a medicinal herb with a diverse range of chemotypes that can exert both anxiolytic and anxiogenic effects on humans. Medical cannabis patients receiving organically grown cannabis from a single source were surveyed about the effectiveness of cannabis for treating anxiety. Patients rated cannabis as highly effective overall for treating anxiety with an average score of 8.03 on a Likert scale of 0 to 10 (0 = not effective, 10 = extremely effective). Patients also identified which strains they found the most or least effective for relieving their symptoms of anxiety. To find correlations between anxiolytic activity and chemotype, the top four strains voted most and least effective were analyzed by HPLC-MS/MS to quantify cannabinoids and GC-MS to quantify terpenes. Tetrahydrocannabinol (THC) and trans-nerolidol have statistically significant correlations with increased anxiolytic activity. Guiaol, eucalyptol, γ-terpinene, α-phellandrene, 3-carene, and sabinene hydrate all have significant correlations with decreased anxiolytic activity. Further studies are needed to better elucidate the entourage effects that contribute to the anxiolytic properties of cannabis varieties.

An integrative systems biology approach for precision medicine in diabetic kidney disease

Current therapeutic approaches are ineffective in many patients with established diabetic kidney disease (DKD), an epidemic affecting one in three patients with diabetes. Early identification of patients at high risk for progression and individualizing therapies have the potential to mitigate kidney complications due to diabetes. To achieve this, a better understanding of the complex pathophysiology of DKD is needed. A system biology approach integrating large-scale omic data is well suited to unravel the molecular mechanisms driving DKD and may offer new perspectives how to personalize therapy. Recent studies indeed show that integrating genome scale data sets generated from prospectively designed clinical cohort studies with model systems using innovative bioinformatics analysis revealed critical molecular pathways in DKD and led to the development of candidate prognostic molecular biomarkers. This review seeks to provide an overview of the recent progress in the application of the integrative systems biology approaches specifically in the field of molecular biomarkers for DKD. We will mainly focus the discussion on how to use integrative system biology approach to first identify patients at high risk of progression, and second to identify patients who may or may not respond to treatment. Challenges and opportunities in applying precision medicine in DKD will also be discussed.

Systems Medicine-Complexity Within, Simplicity Without

This paper presents a brief history of Systems Theory, progresses to Systems Biology, and its relation to the more traditional investigative method of reductionism. The emergence of Systems Medicine represents the application of Systems Biology to disease and clinical issues. The challenges faced by this transition from Systems Biology to Systems Medicine are explained; the requirements of physicians at the bedside, caring for patients, as well as the place of human-human interaction and the needs of the patients are addressed. An organ-focused transition to Systems Medicine, rather than a genomic-, molecular-, or cell-based effort is emphasized. Organ focus represents a middle-out approach to ease this transition and to maximize the benefits of scientific discovery and clinical application. This method manages the perceptions of time and space, the massive amounts of human- and patient-related data, and the ensuing complexity of information.