What signal represents a danger aspect

Basic Types of Signals

Table of contents

The signal is in no way telling the train driver about the states of any of the forthcomming signals, only that the block behind the signal is free, and that the driver may proceed behind the signal to the next signal or to its stop.

Distant signals behaves a bit differently if they use “Absolute block”:
Presignals using absolute block behaves a bit different to presignals using other systems by alarming the approaching train of the states of ALL of the signals it will face using the same signalbox as the presignal. If all signals facing the train are clear, the presignal will be set to clear, however if only one signal are at danger, the presignal will also be at danger. Therefore presignals must be placed BEFORE the first stop signal of the signalbox to have the effect.

For the other working methods, they will warn for the next signal en route, even if that is controlled from another signal box (exception is for “Time interval” system, which also needs to be for the same signalbox)

Placement:
Obviously, presignals are supposed to be placed en route at a distance before the signals they should warn for. The most optimum distance of a presignal in front of its signal (or signal group if it uses absolute block), is the same distance as the braking distance of the train with the longest braking distance.

Multiaspect signals are mostly used with the “track circuit block” system and also possibly the “cab signal” system, however other working methods also make use of more than two aspects:

— “Absolute block”:
The absolute block system uses a signal that is also called a “Combined signal”. This is a three aspect signal, and the third aspect (CAUTION) is controlled from the next signalbox on the line. For this functionality to work, the next signalbox must also be in range of the combined signal, otherwise no presignal aspects are shown.

Placement:
If the signals are set too close to each other, the train might not be able to drive at its full potential due to its braking distance beeing too long. However, if they are spaced out too much, you potentially loose capacity on your tracks.
The optimum distance between multiple aspect signals are for:
— Three aspect signals: longest braking distance of a train.
— Four aspect signals: longest braking distance of a train, divided in 2.
— Five aspect signals: longest braking distance of a train, divided in 3.
The brake distance of a convoy is shown as “brakes from maxspeed” in the vehicle depot.

Placement:
Cab signals are placed like normal track circuit block signals. You can replace any normal 2,3,4 or 5 aspect signal with a cab signal.
Distance for optimum capacity is the longest braking distance of a train.

When a train passes a moving block signal (or beacon), it will drive in the “moving block” working mode. After having passed such a signal or beacon, the train will remain in this working mode until it passes another type of signal (eg a track circuit signal), stops at a station or gets beyond the reach of the last passed beacon (both last cases will make it go to “drive by sight”).

Placement:
A beacon should be placed on the entrence of a doubble tracked line. If there are stations along the line, the train need to pass a new beacon again. If using single tracked lines, be carefull to create a directional reservation BEFORE the train enters the single track, alternatively, use a block reservation (eg a cab signal) at the end of passing loop to create a red reservation until a bidirectional moving block beacon, otherwise deadlocks may arise.

Choose signals serves two functions: They will guide the train to an empty platform at the station, and they will guide a train through a station if the mainline route is occupied. To make use of this second function, you need to place an end of choose sign outside all the exits of the station.
When a train approaches the choose signal, it will try to book a route all the way till its destination platform or the “end of choose” sign, whichever is encountered first. If succeded, the appropriate (main route) message is given to the train. If the initial attempt fails, the choose signal tries to book a route to an alternative platform, or via an alternative route to the end of choose sign. If the second attempt is successful, the appropriate (subsidiary route) message is given to the train. If second attempt also failed, it will show DANGER until any route is free.
The choose signal may also be a multiple aspect signal with the same number of aspects as a normal signal.

Placement:
Choose signals should be placed before the entrance of a station, or before the entrance to the tracks it is “controlling”, preferabley so trains waiting at the signal will not block any outgoing trains.
If you have built a complex station with platforms after each other with junctions in between, choose signals can be used at platform ends to find a free route out of the station, however, it can also lead to strange routes if station is poorly designed.
It is worth investigating how many aspects the choose signal should have. If it is facing a terminus station, there is no need for more than a two aspect choose signal. But if the tracks continue behind the station, one can pick a choose signal with more aspects if traffic demands it.

Permissive signals is used to increase line capacity by letting more trains be inside the same block at once.
When a train has come to a stand at a signal at danger with permissive possibilities, it will be given a “CALL ON” aspect after which it will proceed in drive by sight mode. This allows multiple trains to enter a section, which might be useful in busy goods loops, or low speed high density urban passenger lines. NOTE that the permissive possibility is only allowed when the signal controls a section of unidirectional track with no junctions. If there are junctions, the permissive functionality is disabled and the signal works as an ordinary signal.

Some signals do not show a visible call on aspect: in this case, they will continue to show a danger aspect when the train passes.
In Pak128.Britain-Ex, the sighting speed for the permissive signals is lower than other signals, so there is a real disadvantage in placing them where they do not work as such.

Note to the CLEAR aspect: The number of free blocks ahead depends on whether this is a 2,3,4 or 5 aspect signal, just like a normal multi aspect signal.

Placement:
Permissive signals should be placed where there is no risk at encounting head on traffic, eg at double tracks.
They should NOT be placed before any junctions, otherwise it will not let trains pass in drive by sight.
Multi aspect permissive signals should be placed using the same formula as for normal multi aspect signals.

A directional reservation is created when a train books a route to a bidirectional signal. The directional reservation is then created behind that signal and only ends at the next oneway sign. The working methods that supports directional reservation (and bidirectional signals) are:
track circuit block, cab signalling and moving block.

How to use:
This is how to make a failproof directional reservation:
— At the end of the passing loop, put a singlefaced cab- or track circuit signal (NOT a moving block signal).
— Put a bidirectional cab-, track circuit- or moving block signal as the first signal the train will pass.
— Make sure that both ends of the single tracked stretch have this setup.

Danger signals – damaged-self recognition across the tree of life

Introduction

Multicellular organisms across the tree of life share as common problems injury and infection, against which they must initiate immunity to maintain metabolic homeostasis and integrity. Research devoted to understanding immunity has traditionally focused on the detection of the non-self. For example, the “classical,” adaptive immune response in humans depends mainly on antibodies that serve as receptors of antigens stemming from pathogens or, in the case of transplantation, from the allograft (i.e., the genetically “foreign,” transplanted organ; Wood and Morris, 1995; Alan et al., 2001; Trinchieri and Sher, 2007). Similarly, attempts to understand the inducible responses in plants to herbivory or infection by pathogens generally focus on the detection of the non-self: specific prokaryotic molecules such as flagellin or chitin are perceived as microbe- (or pathogen-) associated molecular patterns (MAMPs/PAMPs), whereas molecules from the saliva, regurgitate or oviposition fluids of herbivores are perceived as herbivore-associated molecular patterns (HAMPs), to then mount adequate resistance responses (Jones and Dangl, 2006; Wu and Baldwin, 2010; Zipfel, 2014).

Specific responses to certain pathogens or herbivores evidently come with the advantage that they allow for highly targeted and, thus, energy-saving responses. However, we argue that this general model of immunity is incomplete as long as we ignore the mechanisms that organisms employ to monitor their integrity and to detect the “damaged self” (Figure 1; Matzinger, 2002; Heil, 2009; Land and Messmer, 2012). In general terms, an immune response cannot be based exclusively on the detection of the non-self, for the following reasons. First, pathogenic microorganisms and insect herbivores are way more diverse than their hosts. Thus, it appears difficult to imagine that a single host can evolve specific receptors to individually detect each of its potential enemies. In fact, there are more than one million species of arthropods described, the majority of which are considered herbivores, but we know only a handful of insect-derived elicitors of plant resistance responses (Wu and Baldwin, 2010). Second, all multicellular animals, plants, and fungi are exposed to the conspecific non-self, at least during sexual reproduction. Female organisms must tolerate invasion by pollen or sperm, which are genetically non-self, and females in most species carry the embryo for a certain time, which is 50% genetically non-self. Yet, neither mammals nor plants abort healthy embryos nor do fungi abort sporangia. Third, even intact, healthy multicellular organisms are colonized by microorganisms, i.e., representatives of the heterospecific non-self. Mammals (including humans) and other animals carry myriads of commensalistic or mutualistic microorganisms in their intestine (Turnbaugh et al., 2007; Kau et al., 2011), plants are regularly colonized by diverse endophytic bacteria, fungi, or viruses (Wilson, 1995; Arnold et al., 2000; Schulz and Boyle, 2005; Partida-Martinez and Heil, 2011), and even fungi can carry bacterial or viral endosymbionts (Partida-Martinez and Hertweck, 2005; Márquez et al., 2007; Partida-Martinez et al., 2007). How do hosts avoid uncontrolled immune responses that are triggered by these microbial associates? Finally, injury requires countermeasures that are completely independent of its causal reason. For example, any type of injury to the outer layers (such as skin, cuticle, or epidermis) of a multicellular organism promotes desiccation and pathogen invasion. Thus, organisms must be able to detect injury based on the perception of endogenous signals, rather than waiting for invaders to signal their presence. In summary, multicellular organisms must be able to detect wounding by perceiving endogenous “danger signals” (or “damage-associated molecular patterns,” DAMPs) and to elicit the corresponding general responses, including wound sealing and the induction of an altered state that allows for a fast and efficient detection of the non-self.

FIGURE 1. Damaged-self recognition. The disintegration of cells (left) releases intracellular molecules to the extracellular space and exposes macromolecules to hydrolytic enzymes from which they are separated in the intact cell. In principle, all these delocalised and newly produced molecules can serve as damage-associated molecular patterns (DAMPs) that prepare the neighboring, intact cell (right) for enemy recognition and wound sealing.

The model of a human immune system that is completely based on the perception of the non-self was challenged when Polly Matzinger and one of us (WGL) proposed the “danger hypothesis,” claiming that endogenous molecular signals of cell stress or injury play an important role in innate and adaptive immunity and in allograft rejection (Land et al., 1994; Matzinger, 1994). The model emerged from two independent sources. (1) The Land group employed data from a clinical trial in transplant patients that provided compelling evidence for immunity (here: alloimmunity-mediated allograft rejection) that is induced by tissue injury (here: allograft injury; Land et al., 1994). (2) Matzinger (1994) used a self-coherent chain of theoretical argumentation and concluded that the self/non-self discrimination theory of immune responses is incomplete. For plants, research efforts nowadays still focus on the detection of the non-self (i.e., HAMPs and PAMPs), although early studies used terms such as “wounding,” “wound response,” or “wound hormone” to denominate defensive responses to herbivory and the involved hormone, jasmonic acid (JA; Green and Ryan, 1972; Ryan, 1974; Graham et al., 1986; Stankovic and Davies, 1998; León et al., 2001).

Here, we first present a short overview on the danger model in mammalian immunology and then draw parallels to the current state of the art in plant science, which basically resembles the discussion that (human) immunology saw 20 years ago. We also review some of the major elements of the signaling cascade that are likely to play a role in the perception and transduction of wound-derived endogenous signals (DAMPs, or “danger signals”) across the tree of life. For example, eATP serves as danger signal and triggers immune responses in mammals (Chen and Nuñez, 2010; Zeiser et al., 2011; Gombault et al., 2013), fish (Kawate et al., 2009), insects (Moreno-Garcia et al., 2014), algae (Torres et al., 2008), plants (Demidchik et al., 2003; Chivasa et al., 2005), and fungi (Medina-Castellanos et al., data not shown). Similarly, fragments of the extracellular matrix are perceived as danger signals in organisms across the eukaryotes (Heil, 2012). Membrane depolarization events, Ca 2+ influx into the cytosol, the formation of reactive oxygen species (ROS) and the transient phosphorylation of mitogen-activated protein kinases (MAPKs) have been reported during the first minutes in wounded or infected tissues of mammals, plants, fungi, and insects (see below). We finish with a short discussion of how likely these parallels are to represent homologies or rather the products of parallel evolution in unrelated organisms that are all under the same selective pressure: the need to reliably detect injury without depending on exogenous signals.

The Danger Model in Mammalian Innate and Adaptive Immunity

In the mammalian immune system, two major layers can be distinguished: the innate and the adaptive immune response. In this context, “adaptive” refers to a phenotypic plasticity that optimizes an individual’s immune system for an acquired, highly specific, antibody-based response to current infection. Whereas the innate response is activated in response to the perception of DAMPs and PAMPs by receptors on pre-existing cells, a major characteristic element of the adaptive response is the proliferation of T- and B-lymphocytes (Figure 2) and their recruitment to the site of current infection. The proliferating B-lymphocytes are equipped with antibodies that very specifically target the antigens that are characteristic of the current invader (Wood and Morris, 1995; Trinchieri and Sher, 2007; Takeuchi and Akira, 2010), thus enabling a central feature of the mammalian immune system: the specific recognition of the invading non-self. Antigen presenting cells (APCs) such as dendritic cells (DCs) are required to stimulate T-helper cells and, consecutively, B-cells and, thus, translate innate immune events into adaptive immune processes. The danger/injury model claims that immunity is originally induced by tissue injury, rather than the presence of the non-self, and thereby adds an additional layer to the early recognition events (Figure 2). Because innate immune responses are simulated by damaged-self recognition, in the end both layers of the mammalian immune response are stimulated by DAMPs (Tamura et al., 2012).

FIGURE 2. The danger model. (A) Main players of the (strongly simplified) danger model are the T-helper cell (T), the B-lymphocyte (B), and the dendritic cell (DC). (B) A somatic cell (SC) becomes destructed and releases DAMPs. The perception of these DAMPs causes the DC to mature to become an antigen-presenting cell (APC) and, thereby, gain immunostimulatory capacities. (C) An activated DC acts as APC and presents the antigen (Ag) to a naive T-cell. (D) The activated T-cell helps the B-lymphocyte, which thereby survives the recognition of the antigen. After Matzinger (2002).

After the discovery of innate immunity (Metchnikoff, 1908) and its re-discovery in the late 1990s of the last century (Lemaitre et al., 1996; Poltorak et al., 1998), the model of DAMP-triggered innate immunity was modified and extended (Land, 1999, 2003; Gallucci and Matzinger, 2001; Matzinger, 2002; Hirsiger et al., 2012). In general terms, it was proposed that endogenous molecules exposed on – or secreted by – stressed cells, or released from dying cells, are recognized by pattern recognition receptor (PRR)-bearing cells of the innate immune system. This recognition promotes inflammatory pathways, other parts of the innate immune system and eventually (in the presence of antigens) adaptive immune responses such as the activation on T-helper cells and B-lymphocytes (Figure 2) or the recruitment of neutrophils (Pittman and Kubes, 2013). Neutrophils are among the first leukocytes to be recruited from the bloodstream. Upon their activation by PAMPs and/or DAMPs, neutrophils follow directional cues, crawl along the vessel walls, exit the vasculature and move to the site of injury in the surrounding tissues (Pittman and Kubes, 2013). T-helper cells are required to support B-lymphocytes, which hypermutate to create new, potentially self-reactive cells and, thus, die if they recognize the antigen without help from active T-helper cells (Matzinger, 2002). These T-helper cells, in turn, require co-stimulation by activated DCs, which process the antigen and present it on their surface to T-cells. Hence, mature DCs act as APCs. In this context, sensing of DAMPs by PRR-bearing DCs promotes their maturation to APCs, which is associated with the acquisition of the capacity to elicit an adaptive immune response. Thus, APCs only co-stimulate T-helper cells when they are activated via PRRs such as Toll-like receptors (TLRs) that sense specific DAMPs (Land, 2003; Gallo and Gallucci, 2013).

Besides their direct contact with T-cells, activated DCs can also release specific cytokines such as interleukin 12 that help naïve CD4 cells to mature into active T-helper cells and, thereby, prime the immune system for the upcoming infection. In other words, the entire machinery that is required to recognize antigens and to mount an adaptive immune response is only activated when APCs, neutrophils, or macrophages sense DAMPs before. An intriguing example of the “raison d’être” of this complicated, multistep machinery is the manner by which epithelial cells of the intestine distinguish commensalistic from pathogenic bacteria. These cells respond to flagellin as a PAMP in a much stronger way when they are exposed to increased levels of eATP (Ivison et al., 2011). Here, the integration of DAMP perception into antigen recognition allows intestinal cells to distinguish damaging pathogens from commensals, which possess the same molecular signatures as pathogens but do not harm body cells. Clearly, the immune response needs active control to avoid collateral damage that might exceed the damage caused by pathogens (Zeiser et al., 2011). Molecular indicators of the destruction of body cells by pathogenic microorganisms are thus used in addition to their biochemical identifiers to distinguish between friends and foes in the human intestinal microflora.

Mammalian DAMPs and Their Perception

The term DAMPs is differently used in the literature and can be replaced, for example, by terms such as “danger signals” or “alarmins.” For this review, we define DAMPs as cell-bound molecules or parts of macromolecules which are hidden from recognition by the immune system under normal physiological conditions. Under conditions of cellular stress or tissue injury, these molecules can either be actively secreted by stressed immune cells, exposed on stressed cells, or passively released into the extracellular environment from dying cells or from the damaged extracellular matrix (Hirsiger et al., 2012; Land, 2012; Gallo and Gallucci, 2013; Wenceslau et al., 2014). In the following, we only present some examples of mammalian DAMPs that represent the different classes, with a main emphasis on those examples for which equivalents have been detected in plants (Table 1). In mammals, DAMPs can even be of tissue-specific nature as, for example, crystals, and uromodulin molecules released by renal tubular damage represent kidney-specific DAMPs (Anders and Schaefer, 2014).

TABLE 1. Classification of mammalian damage-associated molecular patterns (DAMPs) based on their respective receptors and putative equivalents in plants.

We suggest to divide mammalian DAMPs into five classes (Table 1) because they are sensed by distinct members of five families of PRRs: TLRs (Kawai and Akira, 2010), receptor for advanced glycation endproducts (RAGE; Lee and Park, 2013), NOD-like receptors (NLRs; Zhong et al., 2013), RIG-I-like receptors (RLRs; Wu and Chen, 2014), and AIM2-like receptors (ALRs; Wu and Chen, 2014). Class I DAMPs comprise, for example, the important chromatin, high-mobility group protein B1 (HMGB1; Kang et al., 2014; Tsung et al., 2014), or heat shock proteins (HSPs; Seigneuric et al., 2011; Tamura et al., 2012), which are perceived via specific membrane-bound TLRs that act as PRRs and activate MAPK signaling cascades to induce inflammatory cytokines (Figure 3). MAPK signaling cascades are highly conserved elements in all eukaryotic cells that trigger the responses to multiple developmental or environmental stimuli. MAPK signaling cascades consist of three layers of kinases, in which MAPKs are activated via the simultaneous phosphorylation of a tyrosine residue and a threonine residue that are localized in an evolutionarily conserved “Thr-X-Tyr” motif in the activation loop of the MAPK. This phosphorylation is catalyzed by MAPK kinases (MAPPKs) that exhibit specificity both toward their MAPK and their respective upstream MAPKK kinase (MAPKKK). The latter type of enzymes forms a very diverse group of protein kinases that activate MAPKKs by serine/threonine phosphorylation, again in a conserved motif. Among others, MAPK cascades are involved in the perception of diverse DAMPs and PAMPs and, thus, represent central elements in the immune response to damage or infection (Kyriakis and Avruch, 2012).

FIGURE 3. MAPKs in the DAMP perception in innate immune cells. DAMPs interact with multiple PRRs of innate immune cells and trigger the maturation of DC to mature APCs or the synthesis and release of Type I interferons (IFNs), cytokines, chemokines, and other pro-inflammatory compounds. Toll-like receptors (TLRs) such as TLR2 or TLR4 are located on the outer membrane, sense class I DAMPs (such as HMGB1) and initiate a pathway dependent on MyD88 and other mediators that triggers cascades that depend on mitogen-activated protein kinases, MAPKs (among others) and activate NF-κB and other transcription factors (TF). Nucleic acids can also be sensed via TLRs 3,7,8,9, which are located on the endosomal membrane, and activate the same downstream pathways.

Toll-like receptors are also involved in the perception of mitochondrial DNA (mtDNA; Zhang et al., 2010; Simmons et al., 2013) and of cytosolic double-stranded RNA (dsRNA; Amarante and Watanabe, 2010; Nellimarla and Mossman, 2014) and, again, activate downstream MAPK cascades. In DCs, TLRs that are located on the outer membrane sense class I DAMPs and initiate a pathway dependent on Myeloid Differentiation Primary response gene 88 (MyD88) and other mediators, which trigger MAPK cascades (Kyriakis and Avruch, 2012) and lead to the activation of NF-κB and other transcription factors (TF). Similarly, the capacity of eDNA to trigger the synthesis of complement factor B in macrophages in response to endogenous damage depends on HMGB1, MyD88 and NF-κB signaling (Kaczorowski et al., 2012), and the recently discovered DAMP S100A9 is perceived by TLR4 and mediates MyD88 signaling (Tsai et al., 2014).

Class II DAMPs such as ROS, monosodium ureate (MSU; Rock et al., 2013), eATP (Riteau et al., 2012; Gombault et al., 2013) or dsDNA (Patel et al., 2011) are sensed indirectly by the NLRP3 (NOD-like receptor family protein 3) inflammasome (see below) and, like class I DAMPs, are critical signals that are required for the maturation of DCs (Gallo and Gallucci, 2013).

Class III DAMPs comprise MIC-A, MIC-B (stress-induced soluble major histocompatibility complex class I-related chains A/B), and UL-binding proteins (ULBPs; Elsner et al., 2010; Li and Mariuzza, 2014; Nachmani et al., 2014) that are recognized by receptors such as NKG2D, an activating receptor that is expressed by innate lymphocytes such as NK cells and innate-like T-lymphocytes such as gamma delta T-cells.

Class IV DAMPs are defined here as neoantigens such as non-muscle myosin II (NMHC-II), actin cytoskeleton and oxidized phospholipids (Zhang et al., 2006a; Shi et al., 2009; Binder, 2012), all of which bind to pre-existing natural IgM antibodies to activate the complement cascade via the classical lectin receptors and alternative pathways.

Class V DAMPs or “Dyshomeostasis – Associated Molecular Patterns” refer to the recently described “homeostatic danger signals” (Gallo and Gallucci, 2013); they are defined here as an altered pattern of molecules reflecting perturbations in the steady-state of the intra- and/or extracellular microenvironment. These “homeostatic danger signals” include (but are not limited to) hypoxia, changes in acidity or osmolarity, and metabolic stress such as the accumulation of unfolded or misfolded proteins in the endoplasmatic reticulum (ER stress; Gallo and Gallucci, 2013; Garg and Agostinis, 2014).

Activation of the NLRP3 Inflammasome by PAMPs, DAMPs, and ROS

Priming is particularly pertinent to the activation of the NLRP3 inflammasome. The inflammasome is a multiprotein complex existing in innate immune cells such as DCs and macrophages; its exact composition depends on the activating factors and the cell type by which it is harbored. In its active form, the inflammasome is responsible for activation of inflammation and, eventually, programmed cell death. Multiple PAMPs and DAMPs activate the NLRP3 inflammasome, which contains NALPS (NACHT-, LRR-, and PYD-domains-containing protein 3), encoded by the NLRP3 gene. Interestingly, class II DAMPs such as dsDNA can also interact with the class I DAMP, HMGB1 to form a complex that triggers a RGA-mediated activation of the inflammasome (Liu et al., 2014).

Recent research indicates the existence of a priming step and a separate activation step that are required to trigger NLRP3 activity (Figure 4). When class I DAMPs such as HMGB1 or HSPs are sensed via TLRs on macrophages, they trigger the transcription-mediated up-regulation of the NLRP3 receptor, a response that can also be promoted by mitochondrial ROS. Besides the transcription-dependent recruitment of NLRP3, priming also includes the synthesis of the interleukin precursor, pro-IL-1ß (Figure 4A). Finite activation of the inflammasome is provided by class II DAMPs including cholesterol and uric acid crystals or by PAMPs, all of which can be taken up by phagocytosis and then released from lysosomes to trigger ROS-dependent NLRP3 assembly (Figure 4B). Alternatively, NLRP3 assembly can be triggered by K + effluxes and Ca 2+ influxes or by the class II DAMP, eATP (Gombault et al., 2013), which affects NLRP3 via the activation of the P2X7 receptor (Figure 4B). In all cases, NLRP3 assembly triggers the production of IL-1β from pro-IL-1β (among other interleukins), its release from the cell, consecutive sensing via the interleukin receptor (IL-1R), activation of TF such as NF-kB and, finally, gene expression leading to inflammation or, ultimately, cell death (Tschopp and Schroder, 2010; Latz et al., 2013). In short, DAMP-triggered immunity contains a positive feedback loop (here: the upregulation of a DAMP receptor and of the substrate of interferon synthesis after a first exposure to DAMPs), which serves to prime the cell for a faster or stronger response once the stress is repeated. DAMP perception is involved in several parts of the activation process to avoid aberrant activation (Figures 4A,B).

Plant and Mammalian DAMPs

Plants possess no adaptive immune response and, thus, depend only on innate immunity (Jones and Dangl, 2006; Zipfel, 2014). Nevertheless, plants are resistant against most potential herbivores and pathogens and this resistance is due to a myriad of constitutive and inducible defense mechanisms that possess different degrees of specificity (Barrett and Heil, 2012). Induced resistance in plants against natural enemies is mainly controlled via two interacting signaling pathways (Pieterse et al., 2009). The octadecanoid signaling cascade, with the central hormone JA, is mainly directed against herbivores and necrotrophic pathogens (Wasternack, 2007; Campos et al., 2014), whereas biotrophic pathogens are controlled via responses that depend mainly on salicylic acid (SA; Métraux, 2001; Shah, 2003). Both pathways are usually subject to a negative crosstalk, due to which plants normally can mount resistance either to herbivores or to biotrophic pathogens, but not both at the same time (Thaler et al., 2012).

Early research into resistance to chewing herbivores such as beetles and caterpillars, termed the “plant wound response,” used leaf homogenate to elicit defensive responses: a treatment that applies indicators of the damaged self, rather than HAMPs as indicators of the non-self (Green and Ryan, 1972; Ryan, 1974; Turlings et al., 1993; Mattiacci et al., 1995). Disintegrated plants cells release DAMPs that can be sensed by as-yet intact cells and trigger defensive responses, just as we have described above for mammalian DAMPs (Heil, 2009, 2012). Plant DAMPs can be identical to human DAMPs, or represent functional equivalents (Table 1). For example, eATP induces multiple defensive responses in plants (Demidchik et al., 2003; Chivasa et al., 2005, 2009; Kim et al., 2006; Heil et al., 2012; Choi et al., 2014; Tanaka et al., 2014). Similarly, components of the human extracellular matrix serve as important DAMPs (Schaefer, 2010; Docherty and Godson, 2011; Zeiser et al., 2011), and cell wall-derived pectins, oligogalacturonides, and oligosaccharides represent some of the most classical inducers of plant defense responses (Doares et al., 1995; Creelman and Mullet, 1997; Stennis et al., 1998; Bergey et al., 1999; Orozco-Cardenas and Ryan, 1999; León et al., 2001). Pectin methylesterase releases methanol from the pectin in plant cell walls, and methanol acts as a potent volatile DAMP (Dorokhov et al., 2012; Komarova et al., 2014; Hann et al., 2014). It is likely the hydrolysis of cell-wall components that can also trigger JA-dependent defense responses to necrotrophic pathogens (i.e., pathogens that kill the cells of their host and feed on the content of the dead cells). Indeed, the release of oligomers from the polygalacturonate in Arabidopsis plant cell walls via a pectolytic enzyme from the soft-rot pathogen Erwinia sp. induced a gene that is involved in JA synthesis (Norman et al., 1999).

Fragments of human proteins such as collagen or fibronectin (Okamura et al., 2001; Thomas et al., 2007) find their equivalents in the high number of peptide signals in plants (Ryan and Pearce, 2003; Narváez-Vásquez et al., 2005; Chen et al., 2008; Yamaguchi et al., 2011; Albert, 2013; Bartels et al., 2013; Logemann et al., 2013; Ross et al., 2014), whereas the equivalents of the oxidized phospholipids that are considered as human class IV DAMPs (Table 1) are the oxidized lipids that constitute the octadecanoid signaling cascade: the central response in plants to damage caused by chewing herbivores (Schaller et al., 2005; Korneef and Pieterse, 2008; Pieterse et al., 2009). In fact, JA, a central hormone in systemic plant signaling, shows strong structural and biosynthetic homology to human prostaglandins (Ryan and Pearce, 1998; Wasternack, 2007).

Interestingly, the use of a programmable mechanical device (“Mec Worm”) that mimics the spatiotemporal feeding patterns of living herbivores caused lima bean (Phaseolus lunatus) to release a blend of volatile organic compounds (VOCs) that resembled what is seen after insect feeding on the same plant (Mithöfer et al., 2005). Similarly, the application of leaf homogenate to slightly damaged leaves of the same species caused an overall transcriptomic response that was very similar to the response to exogenous JA (Heil et al., 2012). Thus, it seems safe to assume that endogenous DAMPs are sufficient to elicit general plant resistance-related plant responses, at least when the DAMPs are applied/released at sufficient quantities and/or the correct composition. Among others, wounded plant cells release VOCs the earliest of which, called green-leaf volatiles (GLVs), are formed within seconds after injury (Scala et al., 2013). These VOCs can prime systemic parts of the locally damaged plants for future attack (Frost et al., 2007; Heil and Silva Bueno, 2007) and trigger resistance to herbivores and pathogens in neighboring plants (Heil and Karban, 2010), but many of them have also direct antimicrobial properties (Scala et al., 2013). As we discuss below, this double function as signals (at the afferent arc of an innate immune response) and direct antimicrobial agent (at the efferent arc) is a property of many DAMPs, for which reason we suggest that GLVs and other damage-induced plant VOCs represent a further class of DAMPs (Heil, 2014). However, we are not aware of volatile or gaseous equivalents in the known array of mammalian DAMPs.

Plant DAMPs and Their Perception

In order to respond specifically to current attack, plants employ PRRs, the two most common classes of which are surface-localized receptor kinases (RKs) or receptor-like proteins (RLPs) that are commonly characterized by leucine-rich repeats (LRR) motifs. These PRRs perceive both PAMPs and DAMPs and, thus, play a central role in the resistance to pathogens (Zipfel, 2014). However, many plant DAMPs trigger both JA- and SA-mediated responses and, thus, are also involved in the resistance to herbivores (Duran-Flores and Heil, 2014; Ross et al., 2014). Hallmark steps in the perception of herbivory in plants are membrane depolarization events and the formation of electric signals (Maffei et al., 2004, 2007; Fromm and Lautner, 2007), Ca 2+ influxes into the cytosol, the formation of ROS via a membrane-bound NADPH oxidase, and MAPK signaling cascades that ultimately activate TF and, thereby, the expression of resistance-related genes (León et al., 2001; Wu and Baldwin, 2010). Among the known plant MAPKs, the MAPK3/MAPK6 pathway is most commonly reported from the wound response in plants (Smékalová et al., 2014). Two further highly important MAPKs in this context are SA-induced protein kinase (SIPK) and wound-induced protein kinase (WIPK), which trigger the synthesis of JA from membrane-bound linolenic acid in the chloroplast and, thus, the octadecanoid signaling cascade (see Figure 5). In principle, all these steps could be activated via the perception of DAMPs by as-yet unknown receptors. Unfortunately, as to the very best of our knowledge, only few receptors for plant DAMPs have been characterized so far.

One of the most intensively studied plant DAMPs is systemin, a 18 amino acid polypeptide that upon wounding is processed from a 200-amino acid precursor called prosystemin, analogous to the functioning of peptide hormones in mammals (Ryan and Pearce, 1998). Interestingly, the systemin receptor in tomato is a transmembrane protein with LRRs on the extracellular surface, one transmembrane domain and a Thr/Ser kinase domain on the intracellular portion of the receptor (Scheer and Ryan, 2002). That is, it shares common motifs with the TLRs (Kawai and Akira, 2010, 2011) that perceive mammalian class I DAMPs. Recent research shows that systemin is only one example of a large class of small peptide molecules that trigger plant defense (Albert, 2013) and that usually are derived upon damage from precursors that play different roles in the intact tissue (Bartels et al., 2013). In Arabidopsis thaliana, small peptides (ATPeps) are perceived by LRR RKs (Bartels et al., 2013; Logemann et al., 2013), which indicates that the LRR-motif might be a common motif in the receptors of plant peptide DAMPs.

The receptor for eATP was discovered just earlier this year (Choi et al., 2014). The ATP-insensitive Arabidopsis thaliana mutant, dorn1 (does not respond to nucleotides 1), was found to be defective in a lectin receptor kinase. DORN1 is a nucleotide-binding membrane protein with preferred affinity for ATP and is required for the eATP-induced calcium response. In Arabidopsis, Ca 2+ influx triggers the development of ROS (Beneloujaephajri et al., 2013) and elevated levels of ROS activate MAPK3 and MAPK6 (Smékalová et al., 2014). Consequently, the mutant, dorn1, failed to trigger the phosphorylation of MAPK3 and MAPK6 (Choi et al., 2014). For Arabidopsis, eATP, Ca 2+ influxes, ROS signaling, and the activation of MAPK3 were related to each other already in a study showing that levels of cytosolic free Ca 2+ are determined by eATP perception at the plasma membrane and that eATP causes the production of ROS by plasma membrane-bound NADPH oxidase and the enhanced transcription of the MAPK3 gene (Demidchik et al., 2009).

Further receptors for plant DAMPs will have to be searched for in the future. However, circumstantial evidence from multiple plant species makes it tempting to speculate that plant DAMPs are generally perceived by and trigger the same signaling elements as they are known from the perception of PAMPs and HAMPs in plants, or from DAMP perception in mammals. For example, mechanical wounding or the application of conspecific leaf homogenates to common bean (Phaseolus vulgaris) caused the local development of ROS in the treated areas and the secretion of extrafloral nectar, which is a late, JA-dependent response to herbivory (Duran-Flores and Heil, 2014). The secretion of extrafloral nectar also increased after punching holes with a needle into the leaf blade of Macaranga tanarius (Heil et al., 2001), and sterile wounding enhanced the ROS levels in leaves of sweet potato, Ipomoea batatas (Rajendran et al., 2014). The same response was seen, for example, after soft mechanical stress in Arabidopsis (Benikhlef et al., 2013), or after using a razor blade to apply multiple sterile wounds to tomato (Lycopersicon esculentum) leaves (Orozco-Cardenas and Ryan, 1999). In fact, this form of mechanical wounding caused the generation of ROS in plant species in the Solanaceae, Poaceae, Cucurbitaceae, Fabaceae, and Malvaceae and required a functioning octadecanoid signaling cascade, at least in tomato (Orozco-Cardenas and Ryan, 1999).

Mitogen-activated protein kinase cascades represent conserved signaling pathways in the response of eukaryotes to many types of environmental stress and play an important role in DAMP sensing in mammals (Figure 3; Kyriakis and Avruch, 2012). In the Arabidopsis genome, some 20 MAPKs and around 60 upstream MAPKKKs have been identified (Zhang and Klessig, 2001),which makes it tempting to speculate that MAPKs might act in the downstream signaling after the perception of DAMPs by as-yet unknown PRRs. In tobacco (Nicotiana tabacum), wounding alone activates SIPK and MIPK, although virus-derived PAMPs caused a stronger response (Zhang and Klessig, 1998). Silencing these two genes in wild tobacco, N. attenuata, confirmed that they are required for a complete response to wounding and downstream JA signaling (Wu et al., 2007). Application of HAMPs accelerated the wound response in this context, an observation that might have significantly slowed down the search for the DAMPs that must be involved in the responses of plant MAPK signaling to wounding. Indeed, the mutant of the Arabidopsis eATP receptor, dorn1, failed to trigger the phosphorylation of MAPK3 and MAPK6 (Choi et al., 2014), which represents a first case of a direct connection of DAMP perception to MAPK signaling in plants.

DAMPs in Algae and Fungi

Research into plant DAMPs has been slowed down because the research community focused on the handful of known insect- and pathogen-derived elicitors and their role in the perception of the non-self. Even less effort was devoted to deciphering wound recognition and downstream immunity-related responses in other organisms. Thus, we can only present scattered evidence from few systems here, which nevertheless makes us confident to conclude that wound recognition networks share common elements across the tree of life.

Both fungi and macroalgae respond to wounding with the formation of wound plugs that serve to seal the wound. This response can be elicited by mechanical, sterile wounding alone and, thus, clearly depends on the sensing of some kind of DAMP (Weissflog et al., 2008; Hernández-Oñate et al., 2012; Grosser et al., 2014). Unfortunately, we are not aware of many studies that investigated the early signaling events that lead to wound plug formation in algae. As mentioned above, eATP is a common DAMP and in fact, eATP also plays a role in the wound recognition in algae. For example, ATP is locally released from wounded cells of the alga, Dasycladus vermicularis, and experimental application of eATP to intact cells induced the production of H₂O₂ as an important downstream signaling response to wounding in this species (Torres et al., 2008). Similarly, wound-induced volatile compounds play a role in the wound response in the alga, Dictyota dichotoma (Wiesemeier et al., 2007), and waterborne signals can prime brown algae (Laminaria digitata) for faster responses to wounding or herbivore attack (Thomas et al., 2011), just as we have described above for GLVs, methanol and other VOCs that are released from plant wounds.

In the fungus, Trichoderma atroviride, mechanical wounding triggers Ca 2+ influx and the production of ROS by a membrane-bound NADPH oxidase (Hernández-Oñate et al., 2012), and recent evidence now demonstrates that eATP can trigger the same responses and that downstream signaling is mediated via the MAPKs, Tmk1, and Tmk3, which represent the homologs of plant MAPK3 an MAPK6 (Medina-Castellanos et al., data not shown). Interestingly, some diffusible compounds of low molecular weight from fruiting body homogenate induced the development of fruiting bodies as a common wound response in the fungus, Schizophyllum commune (Rusmin and Leonard, 1978), which clearly hints to the involvement of DAMPs in the fungal wound response. In summary, the little evidence that we could find in this context makes it very tempting to speculate that basic steps via which macroalgae and multicellular fungi perceive wounding resemble those that we have described above for mammals and plants.

As mentioned above, most researchers who studied the immune system in mammals or herbivore/pathogen-induced responses in plants focused on the detection of the non-self, whereas little effort was put into the active search for the endogenous danger signals. A further factor that might have hindered research into plant DAMPs is the frequency of seemingly contradictory observations concerning the early responses in plants to wounding. First, many studies report seemingly contradictory observations concerning the relative importance of DAMPs vs. PAMPs or HAMPs in the induction process, which might be in part simply due to the effect that several receptors, and TLRs in particular, interact with different molecules that comprise indicators of both, non-self and damaged-self (Escamilla-Tilch et al., 2013; Peri and Calabrese, 2013). The other way round, in mammals, a single DAMP such as HMBG1 can bind to different PRRs, e.g., TLR and RAGE (Ibrahim et al., 2013), and the same complexity and promiscuity of receptors might exist in plants as well. This high redundancy appears to be required to buffer the immune response against erroneous activation as well as invaders that mutate to achieve a stealthy mode of infection, but it poses significant problems on research as long as we search for linear chains that consist of one ligand, one receptor, and one downstream signaling element.

Furthermore, many potential plant DAMPs (such as systemin or cell wall fragments) appear to be localized both upstream and downstream of generally accepted signaling steps such as Ca 2+ influx, the production of ROS, MAPK cascades and even the classical wound hormone, JA. In the following we discuss some examples of seemingly contradictory reports on signaling elements that are involved in the responses in plants to wounding.

First, a polygalacturonase releases oligogalacturonic acid fragments that trigger ROS production, and the expression of this polygalacturonase was found to respond systemically to local wounding or treatment with MeJA (Orozco-Cardenas and Ryan, 1999). In this scenario, the polygalacturonase appears to act downstream of wound hormone signaling. However, evidence from other studies indicated that oligogalacturonides elicit the formation of ROS (Stennis et al., 1998), thus characterizing their perception as an early event in plant wound signaling. Second, treatment with H₂O₂ can stimulate increases in cytosolic Ca 2+ (Maffei et al., 2006), whereas enhanced cytosolic Ca 2+ activated a potato NADPH oxidase via a Ca-depending protein kinase (Kobayashi et al., 2007) and also was found crucial to trigger the oxidative burst in Arabidopsis (Beneloujaephajri et al., 2013). Thus, Ca 2+ influxes appeared downstream of ROS production in the first study, whereas in the other two studies, Ca 2+ influxes were upstream of ROS production. Third, silencing both SIPK and WIPK in N. attenuata reduced the accumulation of JA after wounding, a reduction that was also reflected in the transcript levels of phytohormone biosynthetic genes and that would place MAPK signaling upstream of the synthesis of wound hormones (Wu et al., 2007). By contrast, a cascade consisting of MAPKK3 and MAPK6 was found to be activated by JA in Arabidopsis (Takahashi et al., 2007), an observation that would place MAPK signaling downstream of the octadecanoid cascade. Fourth, small peptides (Atpeps) represent an emerging class of DAMPs in plants and recent studies showed that the expression of the encoding PROPEP genes is induced when AtPeps are perceived by their corresponding receptors (PEPRs; Logemann et al., 2013; Ross et al., 2014).

In humans, the role of DAMPs in multiple diseases such as hypertension, various cancers, Alzheimer’s disease and diabetes is increasingly being appreciated and again, positive feedback loops represent a common phenomenon. For example, hypertension is associated with end-organ damage, leading to the release of DAMPs that trigger TLR-4 signaling. Since recent evidence suggests that TLR-4 signaling directly affects vascular contractility and, thus, blood pressure (Sollinger et al., 2014), the release of DAMPs appears both as a causal reason and as a consequence of hypertension (McCarthy et al., 2014). Similarly, sterile inflammation can be intensified by positive feedback-loops. For example, histones are released during sterile inflammation, act as DAMPs when they appear in the extracellular space, interact with TLRs to activate the NLRP3 inflammasome and, thereby, contribute to further cell death, which leads to the release of more DAMPs. Thus, it has been discussed that extracellular histones contribute to sepsis, small vessels vasculitis and acute liver, kidney, brain, and lung injury (Allam et al., 2014).

Positive feedback loops and network-like structures, rather than linear cascades, appear to be particularly characteristic of DAMP-mediated signaling and the associated resistance-related events. This positive feedback serves to prime the same cell (see Figures 4A,B) or the surrounding tissue for future injury or infection. In plants, for example, systemin triggers JA-dependent gene expression after wounding in the Solanaceae, and the expression of the gene that encodes prosystemin (the protein from which systemin is liberated after wounding) is induced by JA (Constabel et al., 1995; Ryan and Pearce, 1998; Pearce and Ryan, 2003). Thus, a first wounding event enhances the abundance of prosystemin and, thereby, prepares the plant to respond more strongly to future wounding. Systemin is involved both in the first and in the second part of this circle. This system shows astonishing similarity to the DAMP-induced transcription of the mammalian NLRP3 and Pro-IL-1β genes, which primes the macrophage for a faster and more intensive NLRP3-mediated perception of DAMPs and synthesis of IL-1β once it perceives further DAMPs or PAMPs (Figures 4A,B). Likewise, most of the genes that are involved in JA synthesis are JA-inducible and, hence, their expression is subject to positive feedback (Wasternack, 2007). Thus, the classical upstream-downstream model of signaling is likely not sufficient to understand the perception of DAMPs and the associated signaling events in plants.

Multiple Roles of DAMPs as Resistance Inducers, Antimicrobial Agents, and Modulators of Regeneration

As discussed repeatedly (Dangl et al., 1996; Komarova et al., 2014), wounding is a strong predictor of infection and, therefore, the corresponding signaling must fulfill two non-exclusive functions: preventing infection and triggering the tissue for wound closure and other required responses. The ideal DAMP would fulfill all these functions and, surprisingly enough, many DAMPs have in fact been reported to function as antimicrobial agents and as resistance-inducing signals and/or exert a direct function in tissue regeneration. For example, mammalian type I interferons have direct antiviral activity and are also known for their immunomodulating properties (Gallucci and Matzinger, 2001), HMGB1 acts as class I DAMP, exerts cytokine-like activity (Lee et al., 2014) and stimulated the formation of regenerating fibers and vessel remodeling in the muscles in a mouse model (Campana et al., 2014). Kidney-specific DAMPs not only induce the NLRP3 inflammasome but also triger re-epithelializatian and contribute to the transition of epithelial to mesenchymal cells (Anders and Schaefer, 2014). In plants, DAMPs can trigger a set of basal responses such as cell wall strengthening, which are centrally involved in wound sealing (Delaunois et al., 2014), and ubiquitous DAMPs such as ROS have direct antimicrobial effects and also serve as signals (Dangl et al., 1996; Doke et al., 1996; Lamb and Dixon, 1997; Orozco-Cardenas and Ryan, 1999). Similarly, wound-induced methanol acts as anti-microbial agent and triggers defense responses in neighboring plants (Dorokhov et al., 2012; Komarova et al., 2014). This double function is likely to be a common trait of DAMPs, and in particular of plant VOCs that are released after cell damage. For example, nonanal has direct fungistatic effects (Zeringue et al., 1996) and the same compound induced resistance-gene expression in lima bean to Pseudomonas syringae (Yi et al., 2009). Similarly, methyl jasmonate inhibits the growth and aflatoxin production of Aspergillus flavus (Goodrich-Tanrikulu et al., 1995) and methyl salicylate has been shown to have antifungal activity against Colletotrichum camelliae (Zhang et al., 2006b); both VOCs represent the volatile forms of the resistance hormones, SA and JA, and, thus, their perception is likely to trigger resistance gene expression in most plants that are perceiving them. In general, many VOCs that are induced by herbivory or infection, and particularly GLVs, are well-known for their effects on defense expression, which can include both the direct induction of gene expression (Arimura et al., 2000) as well as its priming (Engelberth et al., 2004; Ton et al., 2007; Yi et al., 2009), and many GLVs and other plant VOCs also have direct antimicrobial effects (Dilantha-Fernando et al., 2005; Scala et al., 2013; Heil, 2014). In short, it is tempting to suggest that future research into potential plant DAMPs should particularly search for compounds that have direct antimicrobial (or, in the case of herbivores: repellent) effects and that also serve as signals that trigger gene expression in both the surrounding and in distant tissues, or organs. Cross-kingdom signaling might be common in this context and can be used by both, plant and plant enemy, for the manipulation of the other partner (Schultz, 2002).

DAMPs Provide the Background for PAMP/HAMP Perception

In spite of all the reports on wound-induced resistance responses in plants, there is a broad agreement across the botanical literature that HAMPs or PAMPs are required to elicit responses as they are seen after herbivore feeding or the infection by pathogens (see, e.g., Wu and Baldwin, 2010, and references cited therein). These seemingly contradictory points of view can be merged when we assume that DAMPs in plants play the same role as in mammals: as co-factors that prime as-yet healthy and intact cells for a full immune response, including the efficient perception of antigens (here: PAMPS and HAMPs). This hypothesis is also in line with the observation that the response to sterile damage in plants is usually correlated with the number of damaged cells: treatments such as the application of leaf homogenates, punching multiple holes with needles or squeezing leaves usually elicit detectable responses, whereas cutting off parts of the leaf blades or entire leaves with scissors or razor blades leaves few damaged cells on the plant and, thus, causes no response, or a response that remains below the detection limit (Heil, 2009).

In fact, most studies in plants found some response to wounding, but stronger responses to pathogen infection or herbivory (or to the application of the corresponding PAMPs or HAMPs into experimentally inflicted, sterile wounds). For example, sterile wounding activated MAPK signaling in tobacco spp., but much stronger responses were observed after the addition of virus particles or insect oral secretions (Zhang and Klessig, 1998; Wu et al., 2007). In an intriguing experiment, the “Mec Worm” device alone induced the formation of ROS but not electrical (V_m) signals or Ca 2+ influx, whereas the V_m response was as strong as seen after caterpillar-inflicted herbivory when caterpillar oral secretions (which contain fatty acid-amino acid conjugates as common HAMPs) were added to the mechanically damaged areas (Bricchi et al., 2010). Similarly, “Mec Worm” induced the release of VOC blends that were qualitatively identical to the herbivore-induced blends with respect to the major compounds (Mithöfer et al., 2005), whereas detailed analysis including minor components revealed that only adding oral secretions to the “Mec Worm”-inflicted damage caused spectra that were indistinguishable from the herbivore-induced ones (Bricchi et al., 2010). Finally, endogenous JA was enhanced after mechanical wounding of sweet potato, whereas feeding by herbivores induced both JA and SA (Rajendran et al., 2014). Thus, we hypothesize that DAMPs provide the necessary biochemical background for the successful perception of HAMPs and for the interpretation of MAMPs as PAMPs in plants and that high doses of chemically complex blends of DAMPs are enough to trigger resistance-responses on their own. This hypothesis is in line with the early observation that preincubation with systemin strongly enhanced the oxidative burst by which tomato cells respond to the exposure to oligogalacturonic acid fragments, which act as DAMPs in this system (Stennis et al., 1998). Tomato cells had been exposed to systemin 12 h before addition of the oligogalacturonides, which, in principle, gave the time for a transcription-based priming as we have described above for the effects of DAMPs in the mammalian NLRP3 inflammasome (Figures 4A,B). Studies aimed at further testing this hypothesis should add DAMPs, HAMPs, or PAMPs in different temporal orders to completely undamaged leaves (rather than adding them to slightly wounded tissues, which inevitably contain at least some DAMPs) and compare the responses to HAMPs or PAMPs in leaves that did, or did not, receive a pre-treatment with HAMPs.

Similarities in Wound Recognition Across the Tree of Life: Homologies or Outcome of Analogous Developments?

In the above-listed examples we emphasized the similarities between DAMP perception in mammals and in other organisms, particularly plants. For example, the systemin-octadecanoid pathway has been characterized early as exhibiting “analogies to arachidonic acid/prostaglandin signaling in animals that leads to inflammatory and acute phase responses” (Ryan and Pearce, 1998) and DAMP-mediated TLR signaling is conserved in vertebrates and invertebrates (Ming et al., 2014). ER stress caused by unfolded or misfolded proteins in the endoplasmatic reticulum is a common trigger of inflammation and other immune responses in mammals (Gallo and Gallucci, 2013; Garg and Agostinis, 2014) whereas in plants, lacking quality control of protein folding in the ER equally can stimulate resistance resonses, likely via DAMP-mediated pathways (Tintor and Saijo, 2014).

Conclusion

The plant, fungal, and the mammalian immune systems are fundamentally different in two aspects. The mammalian system counts with specialized cells that can be equipped with specific sets of receptors and downstream signaling elements to fulfill their detailed function. Moreover, many of these cells are mobile and, thus, can be recruited to the site where their action is needed. By contrast, plants and fungal cells are encapsulated within rigid cell walls and, thus, each cell must be equipped to realize the entire immune response (León et al., 2001). Still, the early mechanisms by which wounding is perceived and downstream immunity-related signaling triggered comprise multiple similar elements. In part, these similarities represent homologies, whereas other parts represent the result of analogous evolution that responds with similar solutions to similar problems. The perception of endogenous danger signals, DAMPs that are released from the own, damaged tissue, represents a hallmark step that is present in all multicellular organisms. DAMPs can have antimicrobial and signaling activities and ensure that adequate responses such as wound sealing and defense against infection are induced almost instantaneously. DAMPs also prime for a more efficient perception of PAMPs/HAMPs and thereby allow to distinguish the harmless non-self (i.e., microbial mutualists and commensals) from the harmful non-self (i.e., pathogens) and to diminish the risk of an erroneous activation of immune responses, which would harm the organism itself. Unfortunately, the role of immunity classically was considered to be only the detection of the non-self. The research into the mammalian immune system has been dramatically slowed down by this narrow focus (Matzinger, 2002). Researchers who are interested in the immune response in plants, fungi or insects, thus, should try to widen the spectrum of signals for which they search and consider DAMPs as an important biochemical background for the perception of the non-self in multicellular organisms across the tree of life.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank Mary B. Mudgett and the entire editorial team at Frontiers in Plant Science for their enthusiastic support for this Research Topic and several colleagues for sharing unpublished manuscripts. Martin Heil acknowledges CONACyT de México for financial support.

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Keywords : danger model, damage-associated molecular pattern, DAMP, immunity, wounding, injury, non-self

Citation: Heil M and Land WG (2014) Danger signals – damaged-self recognition across the tree of life. Front. Plant Sci. 5:578. doi: 10.3389/fpls.2014.00578

Received: 29 June 2014; Accepted: 07 October 2014;
Published online: 31 October 2014.

Mahmut Tör, University of Worcester, UK

Corné M. J. Pieterse, Utrecht University, Netherlands
Stefania Gallucci, Temple University, USA

Copyright © 2014 Heil and Land. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

LMS Speed Signalling

SIGNALS:

LMS Speed Signalling

To the overseas student of railway signalling the concept of speed signalling is not difficult to grasp, but in the UK it is often regarded as something totally alien. Modern British Colour Light signals are incredibly simple in principle but always give an indication of what route a train is to take at a junction. Speed signalling, in contrast, does nothing of the sort – it simply gives information of the speed that a junction may be taken at. Maybe the railways of Britain are just too complex both in layout and by traffic pattern for speed signalling to have ever been practical.

One sole installation of speed signalling was made in Yorkshire by the LMS in 1932. This was installed on a three-mile stretch of quadruple line between Heaton Lodge Junction and Thornhill LNW Junction which included a junction and station at Mirfield. The scheme was for the signals alone, and whilst a little sensible thinning-out of signal boxes occurred, the control remained from mechanical frames and the Absolute Block system continued in use.

All signals in the Mirfield scheme were of the searchlight type, using multiple numbers of heads to achieve the desired combination. A “marker” light was fitted lower down the post; this provided a secondary red light in case of failure of the bulb(s) in the main head.

Three speed terms were used in connection with this system:

Note that the terms Preliminary Caution and Advance Caution used below were in common use but in the official documentation these indications were loosely referred to as Attention indications.

Although speed signalling was never adopted elsewhere in Britain, this small enclave survived until May 1970, when it was swallowed up by a larger power signalling scheme.

Stop signals

A straightforward stop signal, without any junctions ahead, was capable of showing up to five indications – giving very similar indications to the multiple-aspect signals used today.

Indication	Meaning	Route	Indication at next signal
	R-R	Stop	–
Y	Caution	High speed	Stop
Y-Y	Preliminary Caution	High speed	Caution
Y-G	Advance Caution	High speed	Preliminary Caution
G	Clear	High speed	Clear, or Advance Caution

Running Junction signals

At a running junction, a third main head is added to the signal. The top indication applies for “main line” running, whilst the bottom of the three applies to the lower-speed route at the junction, whether it be to left or right. The middle head provides the additional indications for both routes.

These signals were only used for routing between parallel running lines. At physical junctions, multiple-head bracket signals were used – see below.

Indication	Meaning	Route	Indication at next signal
	R-R R	Stop	–
Y-R R	Caution	High speed	Stop
Y-Y-R-R	Preliminary Caution	High speed	Caution
Y-G-R-R	Advance Caution	High speed	Preliminary Caution
G-R-R	Clear	High Speed	Clear, or Advance Caution
R-Y-R	Caution	Medium speed	Stop
R-Y-Y-R	Preliminary Caution	Medium speed	Caution
R-G-R	Clear	Medium speed	Clear, or Preliminary Caution

The system was simplified in 1959 by discontinuing the Advance Caution indication, and two successive Preliminary Caution indications would be displayed if inadequate braking distance existed. It is interesting to note that the Advance Caution indication provided a feature not since catered for by British signalling*. As line speeds continue to increase, demand for an “Outer, Outer Distant” continues to rise, but the present signalling system cannot cope with such a need other than by placing a second double yellow in rear of the one that has insufficient braking distance. This method is flawed by giving the driver the illusion that he must stop sooner than intended – even, perhaps, in a distance that the driver knows is not achievable – leading to excessively hard braking and causing unnecessary worry to drivers.

* – a fifth indication (flashing green) has been used experimentally at locations on the East Coast Main Line for 140 m.p.h. running.

Multi-head Junction signal

At physical junctions, separate signal heads were provided so that the driver had a positive indication of route. This was really a sign that the LMS was not prepared to commit themselves 100% to the principles of speed signalling, fearing problems with wrongly routed traffic.

This example, which represents the Down Slow Starting signal at Mirfield No3, has three dolls:

Left-hand doll	Centre doll	Right-hand doll
	To the Cleckheaton branch	To the Down Slow	To the Down Fast
No marker light was provided because the signal led to a conventionally-signalled area. A yellow aspect acted as the distant signal for Mirfield No4.	A marker light is provided. Only three speed indications are given, because there is no need for a preliminary caution aspect as signal spacing is adequate.	A marker light is provided. Only three speed indications are given, because there is no need for a preliminary caution aspect as signal spacing is adequate.

Splitting Distant signal

Where it was deemed necessary to provide a splitting distant signal to indicate the route cleared at the next signal ahead, things begin to look complicated. Two standard principles of LMS signalling of the era were combined. This was not really a speed signal at all!

The signal shown here represents the Up Advanced Starting signals at Mirfield No1, which led onto a semaphore-signalled area at Heaton Lodge Junction. At Heaton Lodge Junction, the four-track main line continued towards Cooper Bridge, with running junctions between these lines. Four tracks also diverged left towards Huddersfield.

At this time, the LMS used a double-yellow aspect to indicate that a route is clear throughout via a lesser speed route at a junction, whilst green would indicate clear for the faster route. A signal of this type was involved in the Bourne End accident of 1945, and whilst the signalling was not directly implicated the practice of using double-yellow aspects for this purpose was subsequently discontinued.

The LMS also used a three-doll system, which displayed a green light alongside a yellow light. The central lamp was the green, and the yellow lights were illuminated according to the routing circumstances. The combination identified the route cleared – if the green was to the right of a yellow, the right-hand route was cleared, and vice-versa.

Here, on the approaches to Heaton Lodge Junction (and similarly at Thornhill LNW Junction) the two principles were combined to show both the direction to be taken at the junction ahead and whether the train was running via a slow or fast route. The principle can be baffling, but is easier to understand if you keep in mind that the outer lamps are there solely to indicate whether the train is routed to the left or right.

The indications that could be displayed by this signal were as follows:

Indication	Meaning	Route	Indication at next signal
	R	Stop	–
Y	Caution	Stop
G	Clear	Along Up Fast or Along Up Slow to Cooper Bridge (main route)	Clear
Clear	Up Fast to Up Slow or Up Slow to Up Fast to Cooper Bridge (main route via running junction)	Clear
Y	Clear	Up Fast to Up Huddersfield South or Up Fast to Up Huddersfield North or Up Slow to Up Huddersfield South or Up Slow to Up Huddersfield North (branch routes)	Clear

The double-yellow indications were removed by 1960, and their function replaced by the single yellow aspect. This just left the yellow/green combination in place, which survived until the renewal of the signalling in 1970.

Call-on signal

On Permissively-signalled lines, an indication that a train may proceed with the section ahead occupied was given by a miniature yellow light beneath the marker light. The marker light was extinguished when the miniature yellow aspect was lit.

Where a signal read to a Goods Loop signalled on the “No Block” system, a Medium Speed junction signal would be provided, although it would be non-operative. Instead, the Call-on aspect would operate for all trains on that line.

Siding signal

Facing connections into sidings (low speed) were catered for by a miniature green aspect beneath the marker light. The marker light was extinguished when the miniature green aspect was lit.

At most locations, both Siding and Call-on signals would be found below the main aspects. The photograph at the beginning of this article shows a signal of this type, now preserved in the railway museum at Oxenhope on the Keighley & Worth Valley Railway.

Warning arrangement

No separate indication was given to trains accepted under the Warning Arrangement (Regulation 5). They would be brought to a stand at the signal before the signal was cleared, if the line was only clear as far as the next signal with the clearing point fouled.

Boring but true

During 179,508 visits to The Signal Box 931,930 page views have been made since the new web site came into operation on 28th April 2020.

What signal represents a danger aspect

Signals are usually located on the same side as the trains drive. So on countries where trains drive on the left side, such as the United Kingdom, signals are placed left of the track. In countries where trains drive on the right side, such as Germany and the United States, signals are placed right of the track.

Exception is railways with two parallel tracks. In that case they’re placed on left side of the left track, and the right side of the right track.

The UK probably has the easiest signalling system as signals do not give any speed restrictions.

A single green light means clear

A double amber light (two lights above each other) means the next signal is showing a single amber light

A single amber light means the next signal is showing a red light

A red light means danger. You should not pass this signal.

A red light with one or two white lights means danger, but slow speed movements allowed. Basically it means you should drive slow enough to stop for any obstacle. It’s often used whenever the track is occupied by a formation you should be coupling to.

A double flashing amber light is used to let you reduce speed because you’re being diverged into a sideline with a lower speed limit. Static signs should tell you the speed limit. This signal is followed by a single flashing amber light.

A single flashing amber light is used to let you reduce even more speed because you’re being diverged into a sideline with a lower speed limit. The next signal will display an illuminated feather to indicate to which track you’re being diverged. This image shows an example of such a feather signal.[dtl-ghost-storage-bucket-prod.storage.googleapis.com]

A single flashing white light is used to indicate the level crossing ahead is safely closed for road traffic.

or
When a signal is fitted with an illuminated number, the number indicates the track you’re being routed through. It’s used instead of a feather and common on those places with a lot of tracks. Alternatively an alphabetic character may be used to indicate the route being set for you.

Repeater signals are used whenever the view on the next signal is obstructed. Repeater signals indicate the aspect the next signal is displaying. When a repeater signal shows a white light with a horizontal black banner, the next signal is at danger (red) and you should expect to stop.

When a repeater signal shows a white light with a diagonal black banner, the next signal is at caution (amber).

When a repeater signal shows a green light with a diagonal black banner, the next signal is at proceed (green).

There’s two types of semaphores in the UK. Red ones are main signals, indicating wether the line is clear or at danger (comparable to a green, or a red light). Yellow ones are distant signals, indicating the state of the next main signal (comparable to a green, or an amber light). When in a horizontal position, semaphores are in their restrictive position (caution/danger aspect). When in a diagonal position, semaphores are in their safe position (clear). Semaphores may be fitted with small colored lights, but those aren’t as bright as modern light signals.

This is a distant signal giving you a clear aspect. Basically it’s comparable with a green light. UK distant semaphore signals can protect one or more main signals. This distant signal indicates all main signals up to the next distant signal are clear.

This is the main signal giving you a clear aspect. It’s comparable with a green light.

This is a distant signal showing caution aspect. Because distant signals can protect one or more main signals, it’s possible that the next main signal still shows a clear aspect. You should however expect at least one of the main signals to show a danger aspect, until you pass another distant signal.

This is the main signal showing danger aspect. You may not pass. It’s comparable with a red light.

Main signals can also be fitted with a distant signal. In such a case the distant signal will tell you the state of the next main signal. For example:

This is clear aspect on the main signal and another clear aspect on the distant signal. You’re clear to proceed and can expect the next main signals to also be clear.

This is a clear aspect on the main signal, but the distant signal on caution aspect. This means you’re clear to proceed, but should expect to stop at an upcoming main signal.

This is a danger aspect on the main signal. You’re not allowed to pass. You can ask the signaller for permission to pass, but should expect the next main signal also to be at danger.

At yards or switchovers it’s likely that there’ll be multiple semaphore signals. They will be placed next to each other and each represents the routes your train could take. One signal will be located higher than the others and will represent the main line. For example:

The upper signal is showing a clear aspect, which means you will be routed over the main line.

The upper signal is showing danger aspect, but another one is showing a clear aspect. This means you will be routed over to a side track. Many of those have a lower speed limit. There’s usually signs indicating what exactly the speed limit is (or you can rely on the HUD).

«Whistle» sign, most commonly found on modern routes. It tells you you should sound the horn (or whistle, on steam locomotives)

«Sound whistle» sign, most commonly found on historic and heritage routes.

x «Car Stop» sign, you can find several of these on modern platforms, telling you where you should stop based upon the number of cars your consist is made up of.

Found on modern routes, indicates an upcoming speed limit in miles per hour. If the sign shows two numbers, the lower number applies to freight trains, and the higher number applies to passenger trains.

Found on modern routes, indicates a speed limit in miles per hour. If the sign shows two numbers, the lower number applies to freight trains, and the higher number applies to passenger trains.

Found on historic routes, indicates an upcoming speed limit in miles per hour.

Found on historic routes, indicates a speed limit in miles per hour.

In Germany there’s two systems which are pretty similar in how they work, but there’s variations on what the aspects look like. The Vr/Hp signalling system relies on a distant signal, or «Vorsignal» in German, informing you about the state of a main signal, or «Hauptsignal» in German. A distant signals only job is to inform you of the state of the next main signal. As such a distant signal is important as it gives you new information. The main signal should not have any surprises for you.

To warn you a distant signal is near, there are boards with diagonal stripes counting down as you get closer to the distant signal.

Distant signals are marked with a white sign showing two triangles pointing to each other, forming a cross.

On the most common signalling system used in Germany, distant signals have their lights in a diagonal position, which makes them distinguishable even in the dark.

A green-green distant signal means the next main signal is displaying a green light, which means the line is clear and you can proceed.

A green-amber distant signal means the next main signal is displaying a speed restriction. By default this restriction is 40km/h, unless the signal is accompinied by a number.

When a green-amber distant signal is accompinied by a number, located below the signal, the number gives the speed restriction in units of 10km/h. So when the number 6 is displayed, the speed restriction at the next main signal is 60km/h. This number is often an illuminated signal, but could also be an ordinary sign.

An amber-amber distant signal means the next main signal is displaying a red light, which means you need to stop at the next main signal.

In my experience the distance between a distant signal and a main signal is 1km. When a distant signal is accompinied by a smaller white light like in the image above, it means the distance to the main signal is shorter than usual. There are places where there are multiple distant signals before the main signal, especially on places where the line of sight on the main signal is blocked. Any follow-up distant signals will have such a small white light, and will not be announced by the distance beacons (the signs with the stripes counting down).

When approaching a main signal you should not come to any unpleasant surprises, since a distant signal already informed you about the main signals aspect.

A main signal displaying a green light means the line is clear and you can proceed.

A main signal displaying a green and amber light means you’re clear to proceed at a reduced speed. The default speed restriction is 40km/h unless otherwise specified.

When a green-amber main signal is accompinied by a number, the number indicates the speed restriction in units of 10km/h. In the example above, the speed restriction is 60km/h.

A main signal displaying two red lights means danger (stop), and you may not pass the signal.

A main signal displaying one red light and two small white lights means the line is at danger, but you may proceed at very slow speeds. You should drive slow enough to be able to stop for any danger. This signal is often used when the line is occupied by another train to which you must couple.

Main and distant signals are described above are often combined. In such a case the main signal will always be placed on the top, while the distant signal is located directly below. The distant signal displays the state of the next main signal.

This could be all the lights you see at one signal, and looks very complicated. Just split it up in two parts; the upper part is the main signal and should contain no new information. The lower part is the distant signal telling you the state of the next main signal. In this case the main signal is giving you a 80km/h speed restriction and thus you may pass this signal at max 80km/h. The distant signal is indicating a speed restriction of 60km/h, so you should slow down and expect to pass the next main signal no faster than 60km/h.

On some lines the Ks signalling system is used. This signalling system is based on the Vr/Hp system described above, but simplifies aspects by merging the distant signal and the main signal in one signalhead.

A green light means you can pass the next main signal. You can proceed at the maximum allowed speed for the line.

An amber light means you should expect to stop at the next main signal.

A red light means you should stop and not pass this signal.

A red light with two smaller white lights placed in a diagonal position means danger. You may proceed at very low speeds so you can stop for any obstacle you meet. This aspect is often used when the tracks are occupied by a train you should be coupling to.

As with the Vr/Hp signalling system, a small white light at the left side of the signal means the distance to the next main signal is shorter than usual.

A flashing green light with an illuminated yellow number beneath it, means the next main signal shows a speed restriction. Similar to the Vr/Hp system, the number displays the allowed speed in units of 10km/h. In this case you should slow down to 60km/h and not pass the next main signal any faster than 60km/h.

A green light with an illuminated white number above it means the speed restriction starts at this signal. In this case you should not pass this signal any faster than 60km/h.

The signal aspects above can be combined. For example:

The speed restriction starting at this signal is 80km/h, the next main signal will give you a 60km/h speed restriction.

The speed restriction starting at this signal is 60km/h, and you should expect to stop at the next main signal.

A signalhead showing a yellow dot painted on it is used to protect railroad crossings at branch lines. There’s a light located beneath the yellow dot. When the light is off the railroad crossing is not properly closed and you should not pass the railroad crossing.

When the white light flashes the railroad crossing ahead is properly closed and you can safely pass the railroad crossing.

Milage posts are commonly placed at every 200 metres. The upper number is the kilometers, the lower number the units of 100 metres. In above example, it’s 83,6km.

«Halt» sign, indicating where passenger trains should stop on a platform. The sign can be supplemented with a sign indicating a stop position for a «Kurzzug» (short train), «Halfzug» (half train) or «Volzug» (full train), as well as a distance in metres to indicate the length of the trains that should be stopping at this sign.

Whistle sign. The P stands for «Pfeifen», which is the German word for «Whistle»

or
A yellow triangle sign with a black number indicates an upcoming speed limit reduction. These signs are commonly placed 1km ahead of the speed limit reduction. The number indicates the upcoming speed limit in units of 10 km/h (so in this example, «12» indicates 120 km/h.

Line speed limit, in units of 10 km/h. Note that speed restrictions given by signals may still apply.

Unfortunately signalling systems in the US aren’t standardized and every railroad or railroad operator may use their own variants. This makes US signalling pretty hard to learn and explain. There’s signalling charts for several railroad operators on the internet, but in my experience they’re hard to learn and I could never really find a logic in them. In an attempt to make things slightly easier, I’m just going to explain what I’ve learned about US signalling and what tricks I use to remember at least some bacics.

Position lights vs Colored lights
US signals come in many shapes and forms. Most railroads use colored lights, but some use position lights. In TSW the Long Island Rail Road (LIRR) uses position lights.
lights in a horizontal row equals a red light
lights in a diagonal row equals an amber light
lights in a vertical row equals a green light
Position lights could either be yellow or white. Most have 3 lights in a row, but on LIRR there’s some tiny signals located close to the ground which only use 2 lights.

Even though there’s no standard for US signalling, there’s a few signal aspects which are equal to all railroads I’ve seen.

or
When the top signalhead is green and any other signalheads below (when present) are red, it’s clear to proceed. Basically you can ignore any of the red lights. The red lights are only there to let you know the signalhead is functional. So, a green signal equals a green over red, and a green over red over red signal aspect.

or
When the top signalhead is amber and any other signalheads below (when present) are red, it’s a caution aspect where you should expect to stop at the next signal.

or
When all the signalheads are red, not flashing, the signal is showing a danger aspect (stop). Do not pass this signal. This one is easy to remember; Only when it’s all red, then it’s a stop.

or
When one of the signalheads is showing a red flashing lights, and any other signalheads (when present) are red, you’re allowed to proceed at very slow speed. This also applies to when a fully red signal aspect (all red) has an additional white light. These signals are typically used to enter yards, dead ends or track occupied by a formation you should be coupling to. You may need to manually set switches. Drive slow enough to stop for any obstacle you see.

4 SRE Golden Signals (What they are and why they matter)

SRE’s Golden Signals are four key metrics used to monitor the health of your service and underlying systems. We will explain what they are, and how they can help you improve service performance.

What are the Four Golden Signals?

SRE and MonitoringВ

In SRE practices, the major responsibilities of software engineering and operations are to build and improve service reliability and to do so in the most efficient, toil-free way. To improve service reliability, SRE teams generally proactively monitor their service(s) to identify areas that need closer inspection and potential engineering time to improve.В

Monitoring is a critical part of SRE practices. It’s often the starting point for managing the overall system and services reliability. With dashboards of reports and charts, the team can keep an ‘eye out’ for anything unusual. With aggregated data updating dashboards in real-time, one can determine if the 4 golden signals are all green. Monitoring data can be tracked through code pushest to see how each release affects your service.

Monitoring SRE’s Golden SignalsВ

The dilemma of complex distributed systems is that despite being complex, they should be easy to monitor. However, in a complex microservice architecture, it’s difficult to identify the root cause of an issue as different technologies use different components that require expert oversight.В

The golden signals can help consolidate the data received from your many microservices into the most important factors. By reflecting on the most foundational aspects of your service, the four golden signals are the basic building blocks of an effective monitoring strategy. They improve the time to detect (TTD) and the time to resolve (TTR).В В

Latency (Request Service Time)

Latency is the time it takes a system to respond to a request. Both successful and failed requests have latency and it’s vital to differentiate between the latency of successful and failed requests. For example, an HTTP 500 error, triggered because of a connection loss to the database might be served fast. Although, since HTTP 500 is an error indicating failed request, factoring it into the overall latency will lead to misleading calculations. Alternatively, a slow error can be even worse as it factors in even more latency. Therefore, instead of filtering out errors altogether, keep track of the error latency. Define a target for a good latency rate and monitor the latency of successful requests against failed ones to track the system’s health.В

Traffic (User Demand)

Traffic is the measure of how much your service is in demand among users. How this is determined varies depending on the type of business you have. For a web service, traffic measurement is generally HTTP requests per second, while. In a storage system, traffic might be transactions per second or retrievals per second.В

By monitoring user interaction and traffic in the service, SRE teams can usually figure out the user experience with the service and how it’s affected by shifts in the service’s demand.В

Errors (Rate of Failed Requests)

Error is the rate of requests that fail in any of the following ways:В

SRE teams can monitor all errors across the system and at individual service levels to define which errors are critical and which are less severe. By identifying that, they determine the health of their system from the user’s perspective and can take rapid action to fix frequent errors.

Saturation (Overall Capacity of the System)

Saturation refers to the overall capacity of the service or how “full” the service is at a given time. It signifies how much memory or CPU resources your system is utilizing. Many systems start underperforming before they reach 100% utilization. Therefore, setting a utilization target is critical as it will help ensure the service performance and availability to the users.

An increase in latency is often a leading indicator of saturation. Measuring your 99th percentile response time over a small time period can provide an early indicator of saturation. For example, a 99th percentile latency of 60 ms indicates that there’s a 60 ms delay for every one in 100 requests.В

What Should You Do with the Golden Signals?

What makes the golden signals “golden” is that they measure things that represent the most fundamental aspects of your service’s functions. Monitoring large systems gets complicated because there are too many components to monitor, which means more issues and more alerts. To allow developers to focus on other projects, the maintenance burden on the engineers should be minimal.В

The golden signals are mainly used for:

The broad idea is to use your current alerting methods on the signals and track the progress. However, it’s harder to alert using the golden signals as they don’t exactly have a static alerting threshold. Ideally, you should use static thresholds (such as high CPU usage and low memory) but set them realistically to avoid false alerts. For example, the latency of more than 10 seconds, error rates over three per second, etc.В

Basic alerts normally compare the threshold against the average values, but we recommend using percentile or median values. Median values are less sensitive to outliers (big and small) and they reduce the probability of false alerts. In contrast, percentiles show how significant a given value is.

Anomaly DetectionВ

Basic alerting is good enough in normal circumstances, but ideally, you want to use anomaly detection to catch unusual behavior, fast. For example, if your web traffic is 5 times higher at 3 am or drops down to zero in the middle of the day. Besides catching anomalies, it also sets tighter alerting bands to find issues faster than the static thresholds.В

In theory, anomaly detection sounds easy enough, but it can be challenging. Since it’s a fairly new concept, few on-premise monitoring systems currently provide the option. Tools like Prometheus, InfluxDB, DataDog, and SignalFx are some of the tools that offer anomaly detection.В

Tools to Monitor the Golden SignalsВ

Selecting monitoring tools to monitor the golden signals is another critical step in the SRE journey. You can choose between open-source tools and paid tools depending on your specific needs. Both open-source and paid monitoring systems come equipped with dashboards for default metrics and you can also define alerts and notifications.В

Open-source Monitoring Tools

Open-source monitoring tools are a great option if you have a limited tooling budget. In the open-source tools, the source code is accessible to the user, which means that they can customize it to their needs and integrate it into their system. However, customization is not simple and requires time and domain knowledge. Finally, the security, availability, and updates of the tool are also your own responsibility.В

A few great open-source monitoring tools include:

Managed Monitoring Tools

On the other hand, managed tools come at a cost, but also offer robustness that’s missing in the open-source monitoring tools. Here, you’re not responsible for the security, updates, and availability of the monitoring system and also get professional support for their integration.В

Some popular managed monitoring tools are:

Beyond The Golden Signals

Golden signals are a great first step towards understanding and improving incident response. However, many organizations are employing proactive measures to learn more about their system. That includes running simulations to test their system and prepare engineers for various scenarios. These techniques are a great way for SRE teams to learn more about the system and use the information to make it even more reliable.В

Chaos EngineeringВ

Game DayВ

Gameday is another technique that involves simulating a failure event to test the system, processes, and the team’s response. Unlike chaos engineering, game days are geared towards understanding the people and helping them prepare for big failure events. It’s used by many tech giants including Amazon to improve incident response.В

Synthetic User MonitoringВ

Synthetic monitoring is the practice of monitoring your application by simulating users. It enables teams to create artificial users and simulate user behavior to determine their behavior flows. That way, teams can learn more about how the system responds under pressure.В

How can Blameless Help with the Measurement of the Golden Signals?

Blameless can help you make the most out of your monitoring systems and reach your reliability goals. To learn more, request a demo or sign up for the newsletter below.

We hope this blog helped you learn about the four golden signals, but this is really just the start! To get you up to speed with the next level of monitoring, we wrote a new ebook on the subject. It’s totally free, so check it out here!