XTH acts at the microfibril-matrix interface during cell elongation

Sulphorhodamine-labelled oligosaccharides of xyloglucan are incorporated into the cell wall of Arabidopsis and tobacco roots, and of cultured Nicotiana tabacum cells by the transglucosylase (XET) action of XTHs. In the cell wall of diffusely growing cells, the subcellular pattern of XET action revealed a 'fibrillar' pattern, different from the xyloglucan localization. The fibrillar fluorescence pattern had no net orientation in spherical cultured cells. It changed to transverse to the long axis when the cells started to elongate, a feature mirroring the rearrangements of cortical microtubules and the accompanying cellulose deposition. Interference with the polymerization of microtubules and with cellulose deposition inhibited this strong and 'fibrillar'-organized XET-action, whereas interference with actin-polymerization only decreased the intensity of enzyme action. Epidermal cells of a mutant with reduced cellulose synthesis also had low XET action. Root hairs (tip-growing cells) exhibited high XET-action over all their length, but lacked the specific parallel pattern. In both diffuse- and tip-growing cell types extraction of the incorporated fluorescent xyloglucans by a xyloglucan-specific endoglucanase reduced the fluorescence, but the 'fibrillar' appearance in diffuse growing cells was not eliminated. These results show that XTHs act on the xyloglucans attached to cellulose microfibrils. After incorporation of the fluorescent oligosaccharides, the xyloglucans decorate the cellulose microfibrils and become inaccessible to hydrolytic enzymes

Reinforcing the pulmonary artery autograft in the aortic position with a textile mesh: a histological evaluation

OBJECTIVES The Ross procedure involves replacing a patient’s diseased aortic valve with their own pulmonary valve. The most common failure mode is dilatation of the autograft. Various strategies to reinforce the autograft have been proposed. Personalized external aortic root support has been shown to be effective in stabilizing the aortic root in Marfan patients. In this study, the use of a similar external mesh to support a pulmonary artery autograft was evaluated. METHODS The pulmonary artery was translocated as an interposition autograft in the descending thoracic aortas of 10 sheep. The autograft was reinforced with a polyethylene terephthalate mesh (n = 7) or left unreinforced (n = 3). After 6 months, a computed tomography scan was taken, and the descending aorta was excised and histologically examined using the haematoxylin–eosin and Elastica van Gieson stains. RESULTS The autograft/aortic diameter ratio was 1.59 in the unreinforced group but much less in the reinforced group (1.11) (P < 0.05). A fibrotic sheet, variable in thickness and containing fibroblasts, neovessels and foreign body giant cells, was incorporated in the mesh. Histological examination of the reinforced autograft and the adjacent aorta revealed thinning of the vessel wall due to atrophy of the smooth muscle cells. Potential spaces between the vessel wall and the mesh were filled with oedema. CONCLUSIONS Reinforcing an interposition pulmonary autograft in the descending aorta with a macroporous mesh showed promising results in limiting autograft dilatation in this sheep model. Histological evaluation revealed atrophy of the smooth muscle cell and consequently thinning of the vessel wall within the mesh support

Biomechanical evaluation of a personalized external aortic root support applied in the Ross procedure

A commonly heard concern in the Ross procedure, where a diseased aortic valve is replaced by the patient's own pulmonary valve, is the possibility of pulmonary autograft dilatation. We performed a biomechanical investigation of the use of a personalized external aortic root support or exostent as a possibility for supporting the autograft. In ten sheep a short length of pulmonary artery was interposed in the descending aorta, serving as a simplified version of the Ross procedure. In seven of these cases, the autograft was supported by an external mesh or so-called exostent. Three sheep served as control, of which one was excluded from the mechanical testing. The sheep were sacrificed six months after the procedure. Samples of the relevant tissues were obtained for subsequent mechanical testing: normal aorta, normal pulmonary artery, aorta with exostent, pulmonary artery with exostent, and pulmonary artery in aortic position for six months. After mechanical testing, the material parameters of the Gasser-Ogden-Holzapfel model were determined for the different tissue types. Stress-strain curves of the different tissue types show significantly different mechanical behavior. At baseline, stress-strain curves of the pulmonary artery are lower than aortic stress-strain curves, but at the strain levels at which the collagen fibers are recruited, the pulmonary artery behaves stiffer than the aorta. After being in aortic position for six months, the pulmonary artery tends towards aorta-like behavior, indicating that growth and remodeling processes have taken place. When adding an exostent around the pulmonary autograft, the mechanical behavior of the composite artery (exostent + artery) differs from the artery alone, the non-linearity being more evident in the former

Early surgical complications after congenital diaphragmatic hernia repair by thoracotomy vs. laparotomy: A bicentric comparison

Purpose: The surgical strategy for congenital diaphragmatic hernia (CDH) repair remains debated and mainly depends on the training and preference of the surgeon. Our aim was to evaluate the occurrence and nature of surgical reinterventions within the first year of life, following repair through thoracotomy as compared to laparotomy. / Methods: This is a retrospective bi-centric cohort study comparing postero-lateral thoracotomy (n = 55) versus subcostal laparotomy (n = 62) for CDH repair (IRB: MP001882). We included neonates with isolated, left-sided, Bochdalek-type CDH who were operated on between 2000 and 2017, and had a minimum follow-up of 1 year. Excluded were patients treated prenatally and/or had extra-corporeal membrane oxygenation. Outcomes were occurrence and nature of surgical reinterventions and mortality by 1 year of life. / Results: Both groups had comparable neonatal severity risk profiles. The overall surgical reintervention rate by 1 year of age was higher in the thoracotomy group (29.1% vs. 6.5%; p = 0.001), mainly because of a higher prevalence of acute bowel complications (18.1% vs. 3.2%; p = 0.012) requiring surgery, such as perforation, obstruction and volvulus. At 1 year of follow-up, groups were similar in terms of recurrence (5.5% vs. 1.6%; p = 0.341), surgical interventions related to severe gastroesophageal reflux disease (3.6% vs. 1.6%; p = 0.600) and mortality (5.5% vs. 6.6%; p = 1.000). / Conclusion: Postnatal CDH repair through thoracotomy was associated with a higher rate of surgical reinterventions within the first year of life, especially for severe acute gastro-intestinal complications. There seemed to be no difference in recurrence and mortality rate. / Type of Study: Retrospective Comparative Cohort Study. / Level of Evidence: Level III

Federated inference and belief sharing

This paper concerns the distributed intelligence or federated inference that emerges under belief-sharing among agents who share a common world-and world model. Imagine, for example, several animals keeping a lookout for predators. Their collective surveillance rests upon being able to communicate their beliefs-about what they see-among themselves. But, how is this possible? Here, we show how all the necessary components arise from minimising free energy. We use numerical studies to simulate the generation, acquisition and emergence of language in synthetic agents. Specifically, we consider inference, learning and selection as minimising the variational free energy of posterior (i.e., Bayesian) beliefs about the states, parameters and structure of generative models, respectively. The common theme-that attends these optimisation processes-is the selection of actions that minimise expected free energy, leading to active inference, learning and model selection (a.k.a., structure learning). We first illustrate the role of communication in resolving uncertainty about the latent states of a partially observed world, on which agents have complementary perspectives. We then consider the acquisition of the requisite language-entailed by a likelihood mapping from an agent's beliefs to their overt expression (e.g., speech)-showing that language can be transmitted across generations by active learning. Finally, we show that language is an emergent property of free energy minimisation, when agents operate within the same econiche. We conclude with a discussion of various perspectives on these phenomena; ranging from cultural niche construction, through federated learning, to the emergence of complexity in ensembles of self-organising systems

Active Inference and Intentional Behaviour

Recent advances in theoretical biology suggest that basal cognition and sentient behaviour are emergent properties of in vitro cell cultures and neuronal networks, respectively. Such neuronal networks spontaneously learn structured behaviours in the absence of reward or reinforcement. In this paper, we characterise this kind of self-organisation through the lens of the free energy principle, i.e., as self-evidencing. We do this by first discussing the definitions of reactive and sentient behaviour in the setting of active inference, which describes the behaviour of agents that model the consequences of their actions. We then introduce a formal account of intentional behaviour, that describes agents as driven by a preferred endpoint or goal in latent state-spaces. We then investigate these forms of (reactive, sentient, and intentional) behaviour using simulations. First, we simulate the aforementioned in vitro experiments, in which neuronal cultures spontaneously learn to play Pong, by implementing nested, free energy minimising processes. The simulations are then used to deconstruct the ensuing predictive behaviour, leading to the distinction between merely reactive, sentient, and intentional behaviour, with the latter formalised in terms of inductive planning. This distinction is further studied using simple machine learning benchmarks (navigation in a grid world and the Tower of Hanoi problem), that show how quickly and efficiently adaptive behaviour emerges under an inductive form of active inference.Comment: 33 pages, 9 figure

Supervised structure learning

This paper concerns structure learning or discovery of discrete generative models. It focuses on Bayesian model selection and the assimilation of training data or content, with a special emphasis on the order in which data are ingested. A key move - in the ensuing schemes - is to place priors on the selection of models, based upon expected free energy. In this setting, expected free energy reduces to a constrained mutual information, where the constraints inherit from priors over outcomes (i.e., preferred outcomes). The resulting scheme is first used to perform image classification on the MNIST dataset to illustrate the basic idea, and then tested on a more challenging problem of discovering models with dynamics, using a simple sprite-based visual disentanglement paradigm and the Tower of Hanoi (cf., blocks world) problem. In these examples, generative models are constructed autodidactically to recover (i.e., disentangle) the factorial structure of latent states - and their characteristic paths or dynamics