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Stimulating Fungi Pleurotus ostreatus with Hydrocortisone
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Data
July 2021
... Typically, we did not observe any spike trains after the illumination was switched off, however, in a couple of trials we witnessed spike trains on top of the raised potential, as shown in Fig. 5(c). To conclude, living fungal materials respond to illumination by changing their electrical activity, therefore fungal materials can be We demonstrated that hemp pads colonised by the fungus P. ostreatus ( Fig. 6(a)) show distinctive sets of responses to chemical stimulation [11,30]. We stimulated colonised hemp pads with 96% ethanol, malt extract powder (Sigma Aldrich, UK) dissolved in distilled water, dextrose (Ritchie Products Ltd, UK) and hydrocortisone (Solu-Cortef trademark, 4 mL Act-O-Vial, Pfizer, Athens, Greece). ...
... Fungi respond to the application of nutrients by increasing the frequency of electrical potential spiking [11]. Exposure to hydrocortisone leads to a series of electrical disturbance events propagating along the mycelium networks with further indications of suppressed electrical activity [30]. Fungal chemical sensors show a great potential for future applications, however substantial research should be invested in their calibration. ...
... A very low frequency of fungal electronic oscillators does not preclude us from considering inclusion of the oscillators in fully living or hybrid analog circuits embedded into fungal architectures [6] and future specialised circuits and processors made from living fungi functionalised with nanoparticles, as have been illustrated in prototypes of hybrid electronic devices with slime mould [60,55,42,4,20]. Potential devices made of living fungi might include environmental sensors integrated in building structures [6] and wearables [11], patches monitoring chemical parameters of human body [30]. ...
Fungal electronics is a family of living electronic devices made of mycelium bound composites or pure mycelium. Fungal electronic devices are capable of changing their impedance and generating spikes of electrical potential in response to external control parameters. Fungal electronics can be embedded into fungal materials and wearables or used as stand alone sensing and computing devices.
... We demonstrated that hemp pads colonised by the fungus P. ostreatus ( Fig. 6(a)) show distinctive sets of responses to chemical stimulation [11,32]. We stimulated colonised hemp pads with 96% ethanol, malt extract powder (Sigma Aldrich, UK) dissolved in distilled water, dextrose (Ritchie Products Ltd, UK) and hydrocortisone (Solu-Cortef trademark, 4 mL Act-O-Vial, Pfizer, Athens, Greece). ...
... Fungi respond to the application of nutrients by increasing the frequency of electrical potential spiking [11]. Exposure to hydrocortisone leads to a series of electrical disturbance events propagating along the mycelium networks with further indications of suppressed electrical activity [32]. Fungal chemical sensors show a great potential for future applications, however substantial research should be invested in their calibration. ...
Fungal electronics is a family of living electronic devices made of mycelium bound composites or pure mycelium. Fungal electronic devices are capable of changing their impedance and generating spikes of electrical potential in response to external control parameters. Fungal electronics can be embedded into fungal materials and wearables or used as stand alone sensing and computing devices.
... Similarity measures have been widely employed across various disciplines, including machine learning [1,8,10,11], information theory [6,9,16], and computational neuroscience [27]. These measures offer valuable insights into how information is processed and encoded in different contexts. ...
Knowledge distillation (KD) remains challenging due to the opaque nature of the knowledge transfer process from a Teacher to a Student, making it difficult to address certain issues related to KD. To address this, we proposed UniCAM, a novel gradient-based visual explanation method, which effectively interprets the knowledge learned during KD. Our experimental results demonstrate that with the guidance of the Teacher's knowledge, the Student model becomes more efficient, learning more relevant features while discarding those that are not relevant. We refer to the features learned with the Teacher's guidance as distilled features and the features irrelevant to the task and ignored by the Student as residual features. Distilled features focus on key aspects of the input, such as textures and parts of objects. In contrast , residual features demonstrate more diffused attention, often targeting irrelevant areas, including the backgrounds of the target objects. In addition, we proposed two novel metrics: the feature similarity score (FSS) and the relevance score (RS), which quantify the relevance of the distilled knowledge. Experiments on the CIFAR10, ASIRRA, and Plant Disease datasets demonstrate that UniCAM and the two metrics offer valuable insights to explain the KD process.
... Similarity measures have been widely employed across various disciplines, including machine learning [1,8,10,11], information theory [6,9,16], and computational neuroscience [27]. These measures offer valuable insights into how information is processed and encoded in different contexts. ...
Knowledge distillation (KD) remains challenging due to the opaque nature of the knowledge transfer process from a Teacher to a Student, making it difficult to address certain issues related to KD. To address this, we proposed UniCAM, a novel gradient-based visual explanation method, which effectively interprets the knowledge learned during KD. Our experimental results demonstrate that with the guidance of the Teacher's knowledge, the Student model becomes more efficient, learning more relevant features while discarding those that are not relevant. We refer to the features learned with the Teacher's guidance as distilled features and the features irrelevant to the task and ignored by the Student as residual features. Distilled features focus on key aspects of the input, such as textures and parts of objects. In contrast, residual features demonstrate more diffused attention, often targeting irrelevant areas, including the backgrounds of the target objects. In addition, we proposed two novel metrics: the feature similarity score (FSS) and the relevance score (RS), which quantify the relevance of the distilled knowledge. Experiments on the CIFAR10, ASIRRA, and Plant Disease datasets demonstrate that UniCAM and the two metrics offer valuable insights to explain the KD process.
... The strains with high protoplast yield and fast growth rate were chosen as the experimental parents. The yield of protoplasts and growth rate of mycelium from the parent were taken into account [10,11]. ...
Traditional mushroom breeding faces many limitations in improving strains such as insufficient genetic diversity and long breeding cycles. To solve these problems, this study utilized protoplast fusion technology to combine the excellent shapes of different parents to generate strains with new genetic characteristics. The study first optimized the protoplast isolation and fusion conditions of small oyster mushroom and golden mushroom, and then screened and analyzed strain fusions to identify strains with excellent agronomic shapes. The results showed that the protoplast yields of small oyster mushroom X01 and golden mushroom J01 were excellent. These two samples then served as the matrix for strain fusion experiments, and the obtained equations had high reliability. The regeneration rates of small oyster mushroom under single-layer plate culture and liquid-solid phase combined culture were 0.44% and 0.41%, respectively. The regeneration rates of golden mushroom under these two culture conditions were 0.41% and 0.44%, respectively. Based on the results and the convenience of experiment, the single-layer plate culture method was selected as the culture method. In addition, the best inactivation effect of protoplasts was obtained by bathing in water at 50°C for 25 minutes. The fusion was significantly better than the parent strain in terms of growth rate and yield. The results indicated that protoplast fusion technology was an effective tool for improving edible fungi, which could effectively improve the breeding of small oyster mushroom and golden mushroom.
... and challenge a narrative of "technological solutionism, planned obsolescence and consumer capitalism" [18]. Others in unconventional computing research have suggested exploring the use of living materials, like slime mould [3], fungi [21] and bacteria [16], to develop computing systems that are responsive, adaptable, sustainable, and biocompatible. ...
Body perception transformation technologies augment or alter our own body perception outside of our usual bodily experience. As emerging technologies, research on these technologies is limited to proofs-of-concept and lab studies. Consequently, their potential impact on the way we perceive and experience our bodies in everyday contexts is not yet well understood. Through a speculative design inquiry, our multidisciplinary team envisioned utopian and dystopian technology visions. We surfaced potential roles, goals and values that current and future body perception transformation technologies could incorporate, including non-utilitarian purposes. We contribute insights on such roles, goals and values to inspire current and future work. We also present three provocations to stimulate discussions. Finally, we contribute methodologically with insights into the value of speculative design as a fruitful approach for articulating and bridging diverse perspectives in multidisciplinary teams.
... Fungal electronics can be embedded into fungal materials and wearables or used as stand alone sensing and computing devices. In experimental laboratory conditions we demonstrated that fungi can be used as memristors [7], photosensors [8,3], chemical sensors [14,5], humidity sensors [23], and tactile sensors [3]. To make a functional fungal circuits one must connect several fungal electronic devices. ...
Living fungal mycelium networks are proven to have properties of memristors, capacitors and various sensors. To further progress our designs in fungal electronics we need to evaluate how electrical signals can be propagated through mycelium networks. We investigate the ability of mycelium-bound composites to convey electrical signals, thereby enabling the transmission of frequency-modulated information through mycelium networks. Mycelia were found to reliably transfer signals with a recoverable frequency comparable to the input, in the \SIrange{100}{10000} {\hertz} frequency range. Mycelial adaptive responses, such as tissue repair, may result in fragile connections, however. While the mean amplitude of output signals was not reproducible among replicate experiments exposed to the same input frequency, the variance across groups was highly consistent. Our work is supported by NARX modelling through which an approximate transfer function was derived. These findings advance the state of the art of using mycelium-bound composites in analogue electronics and unconventional computing.
... In several challenging signal processing systems [9], [12], [14] and applications, such as machine learning [56], when the data does not follow a Gaussian distribution and the adaptive system is nonlinear, second-order statistics (e.g., variance, correlation, and mean square error) are insufficient to derive adaptive features from the data. Such applications necessitate higher-order statistics of the data, in which the characteristics of linear/nonlinear adaptive signal processing systems, as well as machine learning applications, can be better represented by employing information-theoretic metrics such as entropy, Simpson diversity, expressiveness, and Lempel-Ziv complexity. ...
There is a growing body of studies on applying deep learning to biometrics analysis. Certain circumstances, however, could impair the objective measures and accuracy of the proposed biometric data analysis methods. For instance, people with chronic pain (CP) unconsciously adapt specific body movements to protect themselves from injury or additional pain. Because there is no dedicated benchmark database to analyse this correlation, we considered one of the specific circumstances that potentially influence a person's biometrics during daily activities in this study and classified pain level and pain-related behaviour in the EmoPain database. To achieve this, we proposed a sparsely-connected recurrent neural networks (s-RNNs) ensemble with the gated recurrent unit (GRU) that incorporates multiple autoencoders using a shared training framework. This architecture is fed by multidimensional data collected from inertial measurement unit (IMU) and surface electromyography (sEMG) sensors. Furthermore, to compensate for variations in the temporal dimension that may not be perfectly represented in the latent space of s-RNNs, we fused hand-crafted features derived from information-theoretic approaches with represented features in the shared hidden state. We conducted several experiments which indicate that the proposed method outperforms the state-of-the-art approaches in classifying both pain level and pain-related behaviour.
... In various demanding signal-processing systems and applications, using second-order statistics, such as the mean, variance, and correlation, becomes insufficient when the data deviate from a Gaussian distribution and the adaptive system is nonlinear [37][38][39][40]. In such scenarios, higher-order statistics are necessary to represent the characteristics of linear/nonlinear adaptive signal-processing systems with greater accuracy. ...
The in situ measurement of the bioelectric potential in xilematic and floematic superior plants reveals valuable insights into the biological activity of these organisms, including their responses to lunar and solar cycles and collective behaviour. This paper reports on the “Cyberforest Experiment” conducted in the open-air Paneveggio forest in Valle di Fiemme, Trento, Italy, where spruce (i.e., Picea abies) is cultivated. Our analysis of the bioelectric potentials reveals a strong correlation between higher-order complexity measurements and thermodynamic entropy and suggests that bioelectrical signals can reflect the metabolic activity of plants. Additionally, temporal correlations of bioelectric signals from different trees may be precisely synchronized or may lag behind. These correlations are further explored through the lens of quantum field theory, suggesting that the forest can be viewed as a collective array of in-phase elements whose correlation is naturally tuned depending on the environmental conditions. These results provide compelling evidence for the potential of living plant ecosystems as environmental sensors.
... We have already demonstrated that we achieved in implementing memristors [21], oscillators [22], photosensors [23], pressure sensors [24], chemical sensors [25] and Boolean logical circuits [26] with living mycelium networks. Due to nonlinear electric response of fungal tissues, they are ideally suited for transformation of low-frequency AC signals. ...
We stimulate mycelian networks of oyster fungi Pleurotus ostreatus with low frequency sinusoidal electrical signals. We demonstrate that the fungal networks can discriminate between frequencies in a fuzzy or threshold based manner. Details about the mixing of frequencies by the mycelium networks are provided. The results advance the novel field of fungal electronics and pave ground for the design of living, fully recyclable, electron devices.
... The Fungar project investigates the architectural use of mycelium composites as a combined construction and computing material (Adamatzky et al. 2019). Drawing upon recent findings in the literature that demonstrate bio-electric spiking behaviour in response to environmental stimulation in both the fruiting bodies and mycelium of fungi (Adamatzky 2018;Dehshibi et al. 2021), we hypothesise implementing a data processing circuit within the fungal colony. ...
Proceedings of the Design Modelling Symposium Berlin 2022, Towards Radical Regeneration
... The Fungar project investigates the architectural use of mycelium composites as a combined construction and computing material (Adamatzky et al., 2019). Drawing upon recent findings in the literature that demonstrate bio-electric spiking behaviour in response to environmental stimulation in both the fruiting bodies and mycelium of fungi (Adamatzky, 2018;Dehshibi et al., 2021), we hypothesise implementing a data processing circuit within the fungal colony. ...
In response to global challenges of resource scarcity, increasing attention is being paid to bio-based materials - a domain that covers familiar materials such as timber and emerging materials such as bio-plastics and mycelium composites. The ability to observe, analyse, simulate, and design with their interior heterogeneity and behaviour over time is a necessity for a bio-based and cyclical material practice and opens a deep reservoir of creative and technical innovation potentials within architecture and aligned design practices.This paper describes a research inquiry which seeks to integrate volumetric material data acquired through non-intrusive methods into materially-led digital design workflows. The inquiry is developed as a set of computational tools and approaches to architectural modelling, and demonstrated through three main material tracks: structural glue-laminated timber assemblies, mycelium composites, and bio-luminescent bacteria substrates. Each addresses the acquisition, analysis, and simulation of deep volumetric material data at different scales and in different deployment contexts. In doing so, we demonstrate a novel shift in the digital modelling of bio-based architectural materials and set out its implications for new design practices that deeply embed the individuality and temporality of materials.We contribute a perspective on the possibilities afforded by a volumetric modelling approach to bio-architecture and a computational framework for operating with volume data of heterogeneous materials.
Signaling pathways in fungi offer a profound avenue for harnessing cellular communication and have garnered considerable interest in biomaterial engineering. Fungi respond to environmental stimuli through intricate signaling networks involving biochemical and electrical pathways, yet deciphering these mechanisms remains a challenge. In this review, an overview of fungal biology and their signaling pathways is provided, which can be activated in response to external stimuli and direct fungal growth and orientation. By examining the hyphal structure and the pathways involved in fungal signaling, the current state of recording fungal electrophysiological signals as well as the landscape of fungal biomaterials is explored. Innovative applications are highlighted, from sustainable materials to biomonitoring systems, and an outlook on the future of harnessing fungi signaling in living composites is provided.
Kombucha is a type of tea that is fermented using yeast and bacteria. During this process, a film made of cellulose is produced. This film has unique properties such as biodegradability, flexibility, shape conformability, and ability to self-grow as well as be produced across customized scales. In our previous studies, we demonstrated that Kombucha mats exhibit electrical activity represented by spikes of the electrical potential. We propose using microbial fermentation as a method for in situ functionalization to modulate the electroactive nature of Kombucha cellulose mats, where graphene and zeolite were used for the functionalization. We subjected the pure and functionalized Kombucha mats to mechanical stimulation by applying different weights and geometries. Our experiments demonstrated that Kombucha mats functionalized with graphene and zeolite exhibit memfractive properties and respond to load by producing distinctive spiking patterns. Our findings present incredible opportunities for the in situ development of functionalized hybrid materials with sensing, computing, and memory capabilities. These materials can self-assemble and self-grow after they fuse their living and synthetic components. This study contributes to an emergent area of research on bioelectronic sensing and hybrid living materials, opening up exciting opportunities for use in smart wearables, diagnostics, health monitoring, and energy harvesting applications.
Advancements in mycelium technology, stemming from fungal electronics and the development of living mycelium composites and skins, have opened new avenues in the fusion of biological and artificial systems. This paper explores an experimental endeavour that successfully incorporates living, self-regenerating, and reactive Ganoderma sessile mycelium into a model cyborg figure, creating a bio-cybernetic entity. The mycelium, cultivated using established techniques, was homogeneously grown on the cyborg model’s surface, demonstrating robust reactivity to various stimuli such as light exposure and touch. This innovative merger points towards the future of sustainable biomaterials and the potential integration of these materials into new and existing technologies.
We stimulate mycelian networks of oyster fungi Pleurotus ostreatus with low frequency sinusoidal electrical signals. We demonstrate that the fungal networks can discriminate between frequencies in a fuzzy-like or threshold based manner. Details about the mixing of frequencies by the mycelium networks are provided. The results advance the novel field of fungal electronics and pave ground for the design of living, fully recyclable, electron devices.
This paper provides a conceptual roadmap for the use of hormonal bioinspired models in a broad range of AI, neuroengineering, or computational systems. The functional signaling nature of hormones provides an example of a reliable multidimensional information management system that can solve parallel multitasks. Two existing examples of hormonal computing bioinspired possibilities are shortly reviewed, and two novel approaches are introduced, with a special emphasis on what researchers propose as hormonal computing for neurorehabilitation in patients with complete spinal cord injuries. They extend the use of epidural electrical stimulation (EES) by applying sequential stimulations to limbs through prostheses. The prostheses include various limb models and are connected to a neurostimulation bus called the central pattern generator (CPG). The CPG bus utilizes hormonal computing principles to coordinate the stimulation of the spinal cord and muscles.
Living fungal mycelium networks are proven to have properties of memristors, capacitors and various sensors. To further progress our designs in fungal electronics we need to evaluate how electrical signals can be propagated through mycelium networks. We investigate the ability of mycelium-bound composites to convey electrical signals, thereby enabling the transmission of frequency-modulated information through mycelium networks. Mycelia were found to reliably transfer signals with a recoverable frequency comparable to the input, in the 100Hz to 10 000Hz frequency range. Mycelial adaptive responses, such as tissue repair, may result in fragile connections, however. While the mean amplitude of output signals was not reproducible among replicate experiments exposed to the same input frequency, the variance across groups was highly consistent. Our work is supported by NARX modelling through which an approximate transfer function was derived. These findings advance the state of the art of using mycelium-bound composites in analogue electronics and unconventional computing.
We stimulate mycelian networks of oyster fungi Pleurotus ostreatus with low frequency sinusoidal electrical signals. We demonstrate that the fungal networks can discriminate between frequencies in a fuzzy or threshold based manner. Details about the mixing of frequencies by the mycelium networks are provided. The results advance the novel field of fungal electronics and pave ground for the design of living, fully recyclable, electronic devices.
This work is dedicated to the review and perspective of the new direction that we call "Neuropunk revolution" resembling the cultural phenomenon of cyberpunk. This new phenomenon has its foundations in advances in neuromorphic technologies including memristive and bio-plausible simulations, BCI, and neurointerfaces as well as unconventional approaches to AI and computing in general. We present the review of the current state-of-the-art and our vision of near future development of scientific approaches and future technologies. We call the "Neuropunk revolution" the set of trends that in our view provide the necessary background for the new generation of approaches technologies to integrate the cybernetic objects with biological tissues in close loop system as well as robotic systems inspired by the biological processes again integrated with biological objects. We see bio-plausible simulations implemented by digital computers or spiking networks memristive hardware as promising bridge or middleware between digital and (neuro)biological domains.
A reactive bacterial glove is a cotton glove colonised by Acetobacter aceti, an example of biofabrication of a living electronic sensing device. The bacterial colony, supported by a cellulose-based hydrogel, forms a several millimetres-thick living coating on the surface of the glove. This paper proposes a novel method for analysing the complex electrical activity of trains of spikes generated by a living colony. The proposed method, which primarily focuses on dynamic entropy analysis, shows that the bacterial glove responds to mechanical triaxial stimuli by producing travelling patterns of electrical activity. Kolmogorov complexity further supports our investigation into the evolution of dynamic patterns of such waves in the hydrogel and shows how stimuli initiate electrical activity waves across the glove. These waves are diffractive and ultimately are suppressed by depression. Our experiments demonstrate that living substrates could be used to enable reactive sensing wearable by means of living colonies of bacteria, once the paradigm of excitation wave propagation and reflection is implemented.
A fungal skin is a thin flexible sheet of a living homogeneous mycelium made by a filamentous fungus. The skin could be used in future living architectures of adaptive buildings and as a sensing living skin for soft self-growing/adaptive robots. In experimental laboratory studies we demonstrate that the fungal skin is capable for recognising mechanical and optical stimulation. The skin reacts differently to loading of a weight, removal of the weight, and switching illumination on and off. These are the first experimental evidences that fungal materials can be used not only as mechanical ‘skeletons’ in architecture and robotics but also as intelligent skins capable for recognition of external stimuli and sensorial fusion.
Oyster fungi Pleurotus djamor generate actin potential like spikes of electrical potential. The trains of spikes might manifest propagation of growing mycelium in a substrate, transportation of nutrients and metabolites and communication processes in the mycelium network. The spiking activity of the mycelium networks is highly variable compared to neural activity and therefore can not be analysed by standard tools from neuroscience. We propose original techniques for detecting and classifying the spiking activity of fungi. Using these techniques, we analyse the information-theoretic complexity of the fungal electrical activity. The results can pave ways for future research on sensorial fusion and decision making of fungi.
Smart wearables sense and process information from the user's body and environment and report results of their analysis as electrical signals. Conventional electronic sensors and controllers are commonly, sometimes augmented by recent advances in soft electronics. Organic electronics and bioelectronics, especially with living substrates, offer a great opportunity to incorporate parallel sensing and information processing capabilities of natural systems into future and emerging wearables. Nowadays, fungi are emerging as a promising candidate to produce sustainable textiles to be used as eco-friendly bio wearables. To assess the sensing potential of fungal wearables, we undertook laboratory experiments on the electrical response of a hemp fabric colonised by oyster fungi Pleurotus ostreatus to mechanical stretching and stimulation with attractants and repellents. We have shown that it is possible to discern a nature of stimuli from the fungi electrical responses. The results paved a way towards the future design of intelligent sensing patches to be used in reactive fungal wearables.
For reconstructing CT images in the clinical setting, 'effective energy' is usually used instead of the total X-ray spectrum. This approximation causes an accuracy decline. We proposed to quantize the total X-ray spectrum into irregular intervals to preserve accuracy. A phantom consisting of the skull, rib bone, and lung tissues was irradiated with CT configuration in GATE/GEANT4. We applied inverse Radon transform to the obtained Sinogram to construct a Pixel-based Attenuation Matrix (PAM). PAM was then used to weight the calculated Hounsfield unit scale (HU) of each interval's representative energy. Finally, we multiplied the associated normalized photon flux of each interval to the calculated HUs. The performance of the proposed method was evaluated in the course of Complexity and Visual analysis. Entropy measurements, Kolmogorov complexity, and morphological richness were calculated to evaluate the complexity. Quantitative visual criteria (i.e., PSNR, FSIM, SSIM, and MSE) were reported to show the effectiveness of the fuzzy C-means approach in the segmenting task.
Background:
Phenylalanine ammonia-lyase (PAL, EC 4.3.1.24) is the first key enzyme in the phenylpropanoid pathway. The pal gene has been widely studied in plants and participates in plant growth, development and defense systems. However, in Pleurotus ostreatus, the biological functions of pal during organismal development and exposure to abiotic stress have not been reported.
Results:
In this study, we cloned and characterized the pal1 (2232 bp) and pal2 (2244 bp) genes from the basidiomycete P. ostreatus CCMSSC 00389. The pal1 and pal2 genes are interrupted by 6 and 10 introns, respectively, and encode proteins of 743 and 747 amino acids, respectively. Furthermore, prokaryotic expression experiments showed that PAL enzymes catalyzed the conversion of L-phenylalanine to trans-cinnamic acid. The function of pal1 and pal2 was determined by constructing overexpression (OE) and RNA interference (RNAi) strains. The results showed that the two pal genes had similar expression patterns during different developmental stages. The expression of pal genes was higher in the reproductive growth stage than in the vegetative growth stage. And the interference of pal1 and pal2 delayed the formation of primordia. The results of heat stress assays showed that the RNAi-pal1 strains had enhanced mycelial tolerance to high temperature, while the RNAi-pal2 strains had enhanced mycelial resistance to H2O2.
Conclusions:
These results indicate that two pal genes may play a similar role in the development of P. ostreatus fruiting bodies, but may alleviate stress through different regulatory pathways under heat stress.
We propose that fungi Basidiomycetes can be used as computing devices: information is represented by spikes of electrical activity, a computation is implemented in a mycelium network and an interface is realized via fruit bodies. In a series of scoping experiments, we demonstrate that electrical activity recorded on fruits might act as a reliable indicator of the fungi's response to thermal and chemical stimulation. A stimulation of a fruit is reflected in changes of electrical activity of other fruits of a cluster, i.e. there is distant information transfer between fungal fruit bodies. In an automaton model of a fungal computer, we show how to implement computation with fungi and demonstrate that a structure of logical functions computed is determined by mycelium geometry.
We recorded extra-cellular electrical potential of fruit bodies of oyster fungi Pleurotus djamor. We demonstrated that the fungi generate action potential like impulses of electrical potential. Trains of the spikes are observed. Two types of spiking activity are uncovered: high-frequency (period 2.6 min) and low-frequency (period 14 min); transitions between modes of spiking are illustrated. An electrical response of fruit bodies to short (5 sec) and long (60 sec) thermal stimulation with open flame is analysed in details. We show that non-stimulated fruit bodies of a cluster react to the thermal stimulation, with a single action-potential like spike, faster than the stimulated fruit body does.
With the use of a quantity normally scaled in multifractals, a generalized form is postulated for entropy, namelyS
q
k [1 –
i=1
W
p
i
q
]/(q-1), whereq characterizes the generalization andp
i are the probabilities associated withW (microscopic) configurations (W). The main properties associated with this entropy are established, particularly those corresponding to the microcanonical and canonical ensembles. The Boltzmann-Gibbs statistics is recovered as theq1 limit.
We will discuss fungal communication in the context of fundamental biological functions including mating, growth, morphogenesis, and the regulation of fungal virulence determinants. We will address intraspecies but also interkingdom signaling by systematically discussing the sender of the message, the molecular message, and receiver. Analyzing communication shows the close coevolution of fungi with organisms present in their environment giving insights into multispecies communication. A better understanding of the molecular mechanisms underlying microbial communication will promote our understanding of the "fungal communicome."
The human pathogenic fungus Cryptococcus neoformans has diverged from a common ancestor into three biologically distinct varieties or sibling species over the past 10-40 million years. During evolution of these divergent forms, serotype A C. neoformans var. grubii has emerged as the most virulent and cosmopolitan pathogenic clade. Therefore, understanding how serotype A C. neoformans is distinguished from less successful pathogenic serotypes will provide insights into the evolution of fungal virulence. Here we report that the structurally conserved Pbs2-Hog1 MAP kinase cascade has been specifically recruited as a global regulator to control morphological differentiation and virulence factors in the highly virulent serotype A H99 clinical isolate, but not in the laboratory-generated and less virulent serotype D strain JEC21. The mechanisms of Hog1 regulation are strikingly different between the two strains, and the phosphorylation kinetics and localization pattern of Hog1 are opposite in H99 compared with JEC21 and other yeasts. The unique Hog1 regulatory pattern observed in the H99 clinical isolate is widespread in serotype A strains and is also present in some clinical serotype D isolates. Serotype A hog1delta and pbs2delta mutants are attenuated in virulence, further underscoring the role of the Pbs2-Hog1 MAPK cascade in the pathogenesis of cryptococcosis.
We study long-term electrical resistance dynamics in mycelium and fruit bodies of oyster fungi P. ostreatus. A nearly homogeneous sheet of mycelium on the surface of a growth substrate exhibits trains of resistance spikes. The average width of spikes is c. 23[Formula: see text]min and the average amplitude is c. 1[Formula: see text]k[Formula: see text]. The distance between neighboring spikes in a train of spikes is c. 30[Formula: see text]min. Typically, there are 4–6 spikes in a train of spikes. Two types of electrical resistance spikes trains are found in fruit bodies: low frequency and high amplitude (28[Formula: see text]min spike width, 1.6[Formula: see text]k[Formula: see text] amplitude, 57[Formula: see text]min distance between spikes) and high frequency and low amplitude (10[Formula: see text]min width, 0.6[Formula: see text]k[Formula: see text] amplitude, 44[Formula: see text]min distance between spikes). The findings could be applied in monitoring of physiological states of fungi and future development of living electronic devices and sensors.
We study a cellular automaton (CA) model of information dynamics on a single hypha of a fungal mycelium. Such a filament is divided in compartments (here also called cells) by septa. These septa are invaginations of the cell wall and their pores allow for the flow of cytoplasm between compartments and hyphae. The septal pores of the fungal phylum of the Ascomycota can be closed by organelles called Woronin bodies. Septal closure is increased when the septa become older and when exposed to stress conditions. Thus, Woronin bodies act as informational flow valves. The one-dimensional fungal automaton is a binary-state ternary neighborhood CA, where every compartment follows one of the elementary cellular automaton (ECA) rules if its pores are open and either remains in state 0 (first species of fungal automata) or its previous state (second species of fungal automata) if its pores are closed. The Woronin bodies closing the pores are also governed by ECA rules. We analyze a structure of the composition space of cell-state transition and pore-state transition rules and the complexity of fungal automata with just a few Woronin bodies, and exemplify several important local events in the automaton dynamics.
Hyphae within the mycelia of the ascomycetous fungi are compartmentalised by septa. Each septum has a pore that allows for inter-compartmental and inter-hyphal streaming of cytosol and even organelles. The compartments, however, have special organelles, Woronin bodies, that can plug the pores. When the pores are blocked, no flow of cytoplasm takes place. Inspired by the controllable compartmentalisation within the mycelium of the ascomycetous fungi we designed two-dimensional fungal automata. A fungal automaton is a cellular automaton where communication between neighbouring cells can be blocked on demand. We demonstrate computational universality of the fungal automata by implementing sandpile cellular automata circuits there. We reduce the Monotone Circuit Value Problem to the Fungal Automaton Prediction Problem. We construct families of wires, cross-overs and gates to prove that the fungal automata are P-complete.
A fungal colony maintains its integrity via flow of cytoplasm along mycelium network. This flow, together with possible coordination of mycelium tips propagation, is controlled by calcium waves and associated waves of electrical potential changes. We propose that these excitation waves can be employed to implement a computation in the mycelium networks. We use FitzHugh-Nagumo model to imitate propagation of excitation in a single colony of Aspergillus niger. Boolean values are encoded by spikes of extracellular potential. We represent binary inputs by electrical impulses on a pair of selected electrodes and we record responses of the colony from sixteen electrodes. We derive sets of two-inputs-on-output logical gates implementable the fungal colony and analyse distributions of the gates.
Computed tomography (CT) is a useful and widely employed imaging technique, which represents the largest source of population exposure to ionizing radiation in industrialized countries. Adaptive Statistical Iterative Reconstruction (ASIR) is an iterative reconstruction algorithm with the potential to allow reduction of radiation exposure while preserving diagnostic information. The aim of this phantom study was to assess the performance of ASIR, in terms of a number of image quality indices, when different reconstruction blending levels are employed. CT images of the Catphan-504 phantom were reconstructed using conventional filtered back-projection (FBP) and ASIR with reconstruction blending levels of 20, 40, 60, 80, and 100%. Noise, noise power spectrum (NPS), contrast-to-noise ratio (CNR) and modulation transfer function (MTF) were estimated for different scanning parameters and contrast objects. Noise decreased and CNR increased non-linearly up to 50 and 100%, respectively, with increasing blending level of reconstruction. Also, ASIR has proven to modify the NPS curve shape. The MTF of ASIR reconstructed images depended on tube load/contrast and decreased with increasing blending level of reconstruction. In particular, for low radiation exposure and low contrast acquisitions, ASIR showed lower performance than FBP, in terms of spatial resolution for all blending levels of reconstruction. CT image quality varies substantially with the blending level of reconstruction. ASIR has the potential to reduce noise whilst maintaining diagnostic information in low radiation exposure CT imaging. Given the opposite variation of CNR and spatial resolution with the blending level of reconstruction, it is recommended to use an optimal value of this parameter for each specific clinical application.
A field-effect transistor-based cortisol sensor was demonstrated in physiological condition. Antibody-embedded polymer on the remote gate was proposed to overcome the Debye length issue (λ_D). The sensing membrane was made by linking polystyrene-co-methacrylic acid (PSMA) with anti-cortisol before coating the modified polymer on the remote gate. The embedded receptor in polymer showed sensitivity from 10 fg/ml to 10 ng/ml for cortisol and limit of detection (LOD) of 1 pg/ml in 1× PBS where λ_D is 0.2 nm. LOD of 1 ng/ml was shown in lightly buffered artificial sweat. Finally, a sandwich ELISA confirmed antibody binding activity of antibody-embedded PSMA.
Background: Hair cortisol analysis has been shown to be an effective measure of chronic stress. Cortisol is assumed to incorporate into hair via serum, sebum, and sweat sources; however, the extent to which sweat contributes to hair cortisol content is unknown. Methods: Sweat and saliva samples were collected from 17 subjects after a period of intensive exercise and analyzed by salivary enzyme-linked immunosorbent assay (ELISA). Subsequently, an in vitro test on exposure of hair to hydrocortisone was conducted. Residual hair samples were immersed in a 50-ng/mL hydrocortisone solution for periods lasting 15 minutes to 24 hours, followed by a wash or no-wash condition. Hair cortisol content was determined using our modified protocol for a salivary ELISA. Results: Postexercise control sweat cortisol concentrations ranged from 8.16 to 141.7 ng/mL and correlated significantly with the log-transformed time of day. Sweat cortisol levels significantly correlated with salivary cortisol concentrations. In vitro hair exposure to a 50-ng/mL hydrocortisone solution (mimicking sweat) for 60 minutes or more resulted in significantly increased hair cortisol concentrations. Washing with isopropanol did not affect immersion-increased hair cortisol concentrations. Conclusions: Human sweat contains cortisol in concentrations comparable with salivary cortisol levels. This study suggests that perfuse sweating after intense exercise may increase cortisol concentrations detected in hair. This increase likely cannot be effectively decreased with conventional washing procedures and should be considered carefully in studies using hair cortisol as a biomarker of chronic stress.
Book together with Dekking, Kraaikamp and Meester
Probability and Statistics are studied by most science students, usually as a second- or third-year course. Many current texts in the area are just cookbooks and, as a result, students do not know why they perform the methods they are taught, or why the methods work. The strength of this book is that it readdresses these shortcomings; by using examples, often from real-life and using real data, the authors can show how the fundamentals of probabilistic and statistical theories arise intuitively. It provides a tried and tested, self-contained course, that can also be used for self-study.
A Modern Introduction to Probability and Statistics has numerous quick exercises to give direct feedback to the students. In addition the book contains over 350 exercises, half of which have answers, of which half have full solutions. A website at www.springeronline.com/1-85233-896-2 gives access to the data files used in the text, and, for instructors, the remaining solutions. The only pre-requisite for the book is a first course in calculus; the text covers standard statistics and probability material, and develops beyond traditional parametric models to the Poisson process, and on to useful modern methods such as the bootstrap.
This will be a key text for undergraduates in Computer Science, Physics, Mathematics, Chemistry, Biology and Business Studies who are studying a mathematical statistics course, and also for more intensive engineering statistics courses for undergraduates in all engineering subjects.
Hair cortisol analysis has been shown to be an effective measure of chronic stress. Cortisol is assumed to incorporate into hair via serum, sebum, and sweat sources; however, the extent to which sweat contributes to hair cortisol content is unknown.
Sweat and saliva samples were collected from 17 subjects after a period of intensive exercise and analyzed by salivary enzyme-linked immunosorbent assay (ELISA). Subsequently, an in vitro test on exposure of hair to hydrocortisone was conducted. Residual hair samples were immersed in a 50-ng/mL hydrocortisone solution for periods lasting 15 minutes to 24 hours, followed by a wash or no-wash condition. Hair cortisol content was determined using our modified protocol for a salivary ELISA.
Postexercise control sweat cortisol concentrations ranged from 8.16 to 141.7 ng/mL and correlated significantly with the log-transformed time of day. Sweat cortisol levels significantly correlated with salivary cortisol concentrations. In vitro hair exposure to a 50-ng/mL hydrocortisone solution (mimicking sweat) for 60 minutes or more resulted in significantly increased hair cortisol concentrations. Washing with isopropanol did not affect immersion-increased hair cortisol concentrations.
Human sweat contains cortisol in concentrations comparable with salivary cortisol levels. This study suggests that perfuse sweating after intense exercise may increase cortisol concentrations detected in hair. This increase likely cannot be effectively decreased with conventional washing procedures and should be considered carefully in studies using hair cortisol as a biomarker of chronic stress.
Everyday lifestyle related issues are the main cause of psychological stress, which contributes to health disparities experienced by individuals. Prolonged exposure to stress leads to the activation of signaling pathways from the brain that leads to release of cortisol from the adrenal cortex. Various biomarkers have been affected by psychological stress, but cortisol "a steroid hormone" is known as a potential biomarker for its estimation. Cortisol can also be used as a target analyte marker to determine the effect of exposure such as organophosphates on central nervous system, which alters the endocrine system, leading to imbalance in corbsol secretion. Cortisol secretion of individuals depends on day night cycle and field environment hence its detection at point-of-care (POC) is deemed essential to provide personalized healthcare. Chromatographic techniques have been traditionally used to detect cortisol. The issues relating to assay formation, system complexity, and multistep extraction/purification limits its application in the field. In order to overcome these issues and to make portable and effective miniaturized platform, various immunoassays sensing strategies are being explored. However, electrochemical immunosensing of cortisol is considered as a recent advancement towards POC application. Highly sensitive, label-free and selective cortisol immunosensor based on microelectrodes are being integrated with the microfluidic system for automated diurnal cortisol monitoring useful for personalized healthcare. Although the reported sensing devices for cortisol detection may have a great scope to improve portability, electronic designing, performance of the integrated sensor, data safety and lifetime for point-of-care applications, This review is an attempt to describe the various cortisol sensing platforms and their potential to be integrated into a wearable system for online and continuous monitoring of cortisol rhythm at POC as a function of one's environment.
Prerequisites from Quantum Mechanics.- Information and its Measures.- Entanglement.- More About Information Quantities.- Quantum Compression.- Channels and Their Capacity.- Hypothesis Testing.- Coarse-grainings.- State Estimation.- Appendix: Auxiliary Linear and Convex Analysis.
Bell System Technical Journal, also pp. 623-656 (October)
Local maximum likelihood estimation is a nonparametric counterpart of the widely used parametric maximum likelihood technique. It extends the scope of the parametric maximum likelihood method to a much wider class of parametric spaces. Associated with this nonparametric estimation scheme is the issue of bandwidth selection and bias and variance assessment. This paper provides a unified approach to selecting a bandwidth and constructing confidence intervals in local maximum likelihood estimation. The approach is then applied to least squares nonparametric regression and to nonparametric logistic regression. Our experiences in these two settings show that the general idea outlined here is powerful and encouraging.
Cells need to adapt to the external environment in order to survive. Signal transduction pathways are crucial mechanisms that allow cells to sense and respond to extracellular stimuli. Among the signal transduction pathways, we point out the cascades mediated by mitogen-activated protein kinases (MAPKs). The MAPKs are conserved from yeast to human and play relevant roles in the physiology of the cell. In pathogenic fungi these MAPK pathways control virulence factors. This review describes the MAPK cascades described in Candida albicans, the most frequently isolated fungus, from fungal systemic infections among individuals in developed countries.
Removal of free calcium ions from the incubation medium of isolated bovine adrenocortical cells with EGTA reduced basal cortisol synthesis and blocked the effects of ACTH; additional calcium restored normal steroid synthesis. Calcium channel blockers, verapamil and nitrendipine and the calmodulin antagonist, trifluoperazine inhibited ACTH-stimulated cortisol synthesis in a dose-dependent manner (IC50s of 6.2, 10 and 5.2 microM, respectively). Steroidogenic effects of dibutyryl cyclic AMP were prevented with 50 microM verapamil or trifluoperazine. Calcium ionophore A23187 at 1 microM increased cortisol synthesis 2-3 fold which was less than the normal response to ACTH. Stimulatory effects of ionophore and cyclic AMP or ACTH were not additive. ACTH-stimulation of cortisol synthesis appears to involve cyclic AMP-dependent uptake of extracellular calcium ions, possibly by a mechanism requiring calmodulin. Increases in intracellular calcium ions cannot wholly mimic ACTH actions.
We tested the hypothesis that the inhibitory effect of cortisol on bone growth is primarily on the periosteum. Fetal rat calvaria were maintained in organ culture, labeled with radioactive proline or thymidine, and then dissected to separate periosteum from the osteoblast-rich central bone. There was a dose- and time-dependent inhibition of thymidine incorporation into DNA in the periosteum which was significant at 24 h. These observations were further supported by decreases in the dry weight and DNA content of the periosteum at 96 h. Incorporation of thymidine and proline into the central bone were decreased only at 96 h. Pulse-chase studies using a high concentration of cortisol (10(-6) M) indicated that increased cell attrition may also play a role in the inhibitory effect of cortisol. We propose that the primary effect of cortisol on bone growth is an inhibition of proliferation of the periosteal cells which give rise to osteoblasts. The subsequent decrease in the incorporation of proline into the central bone may be the consequence of this inhibition.
We demonstrate by means of several examples that an easily calculable measure of algorithmic complexity c which has been introduced by Lempel and Ziv [IEEE Trans. Inf. Theory IT-22, 25 (1976)] is extremely useful for characterizing spatiotemporal patterns in high-dimensionality nonlinear systems. It is shown that, for time series, c can be a finer measure for order than the Liapunov exponent. We find that, for simple cellular automata, pattern formation can be clearly separated from a mere reduction of the source entropy and different types of automata can be distinguished. For a chain of coupled logistic maps, c signals pattern formation which cannot be seen in the spatial correlation function alone.
The ability to adapt to altered availability of free water is a fundamental property of living cells. The principles underlying osmoadaptation are well conserved. The yeast Saccharomyces cerevisiae is an excellent model system with which to study the molecular biology and physiology of osmoadaptation. Upon a shift to high osmolarity, yeast cells rapidly stimulate a mitogen-activated protein (MAP) kinase cascade, the high-osmolarity glycerol (HOG) pathway, which orchestrates part of the transcriptional response. The dynamic operation of the HOG pathway has been well studied, and similar osmosensing pathways exist in other eukaryotes. Protein kinase A, which seems to mediate a response to diverse stress conditions, is also involved in the transcriptional response program. Expression changes after a shift to high osmolarity aim at adjusting metabolism and the production of cellular protectants. Accumulation of the osmolyte glycerol, which is also controlled by altering transmembrane glycerol transport, is of central importance. Upon a shift from high to low osmolarity, yeast cells stimulate a different MAP kinase cascade, the cell integrity pathway. The transcriptional program upon hypo-osmotic shock seems to aim at adjusting cell surface properties. Rapid export of glycerol is an important event in adaptation to low osmolarity. Osmoadaptation, adjustment of cell surface properties, and the control of cell morphogenesis, growth, and proliferation are highly coordinated processes. The Skn7p response regulator may be involved in coordinating these events. An integrated understanding of osmoadaptation requires not only knowledge of the function of many uncharacterized genes but also further insight into the time line of events, their interdependence, their dynamics, and their spatial organization as well as the importance of subtle effects.
This meeting took place at the Juan March Foundation, Madrid, Spain, between 3 and 5 November 2003. It was sponsored by the Juan March Foundation and organized by E. Olson and J.M. Redondo.
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Calcineurin is a serine‐ and threonine‐specific protein phosphatase that is conserved in all eukaryotes and is unique among phosphatases for its ability to sense Ca2+ through its activation by calmodulin. Identified and characterized in pioneering work by the Claude Klee and Philip Cohen laboratories in the late 1970s, calcineurin catapulted to centre stage when the groups of Stuart Schreiber and Irving Weissman discovered that it is the target of the immunosuppressants cyclosporin A and FK506. In the same year, the laboratory of Gerald Crabtree showed that cyclosporin blocks the nuclear import of the nuclear factor of activated T cell (NFAT) proteins and in 1993, the group of Anjana Rao showed that these proteins are dephosphorylated by calcineurin. These findings revealed a central pathway that coupled calcineurin to transcriptional regulation (Fig 1). Since then, calcineurin and NFAT proteins have been shown to participate in signalling cascades that govern the development and function of the immune, nervous, cardiovascular and musculoskeletal systems. Parallel advances made in microbial systems, including model yeasts and pathogenic fungi, have revealed that the basic mechanisms of action of calcineurin are conserved from unicellular to multicellular eukaryotes.
Figure 1.
Signal integration and coincidence detection by assembly of NFATc transcriptional complexes in the nucleus. A range of signalling pathways are integrated in the nucleus by the assembly of NFATc transcriptional complexes from calcineurin‐dependent NFATc subunits and inducible nuclear partners (NFATn), which regulate the affinity and specificity of NFATc DNA binding and ensure transcriptional activation in response to two signals. This mechanism allows the complexes to behave as coincidence detectors and signal integrators. CK1, casein kinase 1; Csp1, calcipressin …
[1]: /embed/graphic-1.gif
A method is developed for representing any communication system geometrically. Messages and the corresponding signals are points in two "function spaces," and the modulation process is a mapping of one space into the other. Using this representation, a number of results in communication theory are deduced concerning expansion and compression of bandwidth and the threshold effect. Formulas are found for the maxmum rate of transmission of binary digits over a system when the signal is perturbed by various types of noise. Some of the properties of "ideal" systems which transmit at this maxmum rate are discussed. The equivalent number of binary digits per second for certain information sources is calculated.
Starting with a real-valued N-point discrete-time signal,
frequency-domain algorithms are provided for computing (1) the
complex-valued standard N-point discrete-time “analytic”
signal of the same sample rate; (2) the complex-valued decimated
N/2-point discrete-time “analytic” signal of half the
original sample rate; and (3) the complex-valued interpolated NM-point
discrete-time “analytic” signal of M times the original
sample rate. Special adjustment of the transform end points are shown to
be necessary in order to generate proper discrete-time
“analytic” signals
Capacitive storage in mycelium substrate
- A E Beasley
- A L Powell
- A Adamatzky
Beasley, A. E.; Powell, A. L.; Adamatzky, A. Capacitive storage in
mycelium substrate. arXiv 2020, 2003.07816.
Fungal architecture position paper
- A Adamatzky
- P Ayres
- G Belotti
- H Wösten
Adamatzky, A.; Ayres, P.; Belotti, G.; Wösten, H. Fungal
architecture position paper. Int. J. Unconventional Computing 2019, 14,
397−411.
On measures of entropy and information
- A Rényi
Rényi, A. On measures of entropy and information. In
Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics
and Probability, Vol. 1: Contributions to the Theory of Statistics;
University of California Press, 1961; pp 547−561.