Ligation of protease-activated receptor 1 enhances alpha(v)beta(6) integrin-dependent TGF-beta activation and promotes acute lung injury

Activation of latent TGF-beta by the alpha(v)beta(6) integrin is a critical step in the development of acute lung injury. However, the mechanism by which a alpha(v)beta(6)-mediated TGF-beta activation is regulated has not been identified. We show that thrombin, and other agonists of protease-activated receptor 1(PAR1), activate TGF-beta in an alpha(v)beta(6) integrin-specific manner. This effect is PART specific and is mediated by RhoA and Rho kinase. Intratracheal instillation of the PART-specific peptide TFLLRN increases lung edema during high-tidal-volume ventilation, and this effect is completely inhibited by a blocking antibody against the alpha(v)beta(6) integrin. Instillation of TFLLRN during high-tidal-volume ventilation is associated with increased pulmonary TGF-beta activation; however, this is not observed in Itgb6(-/-) mice. Furthermore, Itgb6(-/-) mice are also protected from ventilator-induced lung edema. We also demonstrate that pulmonary edema and TGF-beta activity are similarly reduced in Par1(-/-) mice following bleomycin-induced lung injury. These results suggest that PART-mediated enhancement of a alpha(v)beta(6)-dependent TGF-beta activation could be one mechanism by which activation of the coagulation cascade contributes to the development of acute lung injury, and they identify PART and the alpha(v)beta(6) integrin as potential therapeutic targets in this condition

Maternal experiences of caring for an infant with neurological impairment after neonatal encephalopathy in Uganda: a qualitative study

Purpose: The study investigated maternal experiences of caring for a child affected by neurological impairment after neonatal encephalopathy (NE) (“birth asphyxia”) in Uganda. Methods: Between September 2011 and October 2012 small group and one-on-one in-depths interviews were conducted with mothers recruited to the ABAaNA study examining outcomes from NE in Mulago hospital, Kampala. Data were analysed thematically with the aid of Nvivo 8 software. Findings: Mothers reported caring for an infant with impairment was often complicated by substantial social, emotional and financial difficulties and stigma. High levels of emotional distress, feelings of social isolation and fearfulness about the future were described. Maternal health-seeking ability was exacerbated by high transport costs, lack of paternal support and poor availability of rehabilitation and counselling services. Meeting and sharing experiences with similarly affected mothers was associated with more positive maternal caring experiences. Conclusion: Mothering a child with neurological impairment after NE is emotionally, physically and financially challenging but this may be partly mitigated by good social support and opportunities to share caring experiences with similarly affected mothers. A facilitated, participatory, community-based approach to rehabilitation training may have important impacts on maximising participation and improving the quality of life of affected mothers and infants. Implications for Rehabilitation Caring for an infant with neurological impairment after NE in Uganda has substantial emotional, social and financial impacts on families and is associated with high levels of emotional stress, feelings of isolation and stigma amongst mothers. Improved social support and the opportunity to share experiences with other similarly affected mothers are associated with a more positive maternal caring experience. High transport costs, lack of paternal support and poor availability of counselling and support services were barriers to maternal healthcare seeking. Studies examining the feasibility, acceptability and impact of early intervention programmes are warranted to maximise participation and improve the quality of life for affected mothers and their infants

Performance Enhancement of Deep Reinforcement Learning Networks using Feature Extraction

The combination of Deep Learning and Reinforcement Learning, termed Deep Reinforcement Learning Networks (DRLN), offers the possibility of using a Deep Learning Neural Network to produce an approximate Reinforcement Learning value table that allows extraction of features from neurons in the hidden layers of the network. This paper presents a two stage technique for training a DRLN on features extracted from a DRLN trained on a identical problem, via the implementation of the Q-Learning algorithm, using TensorFlow. The results show that the extraction of features from the hidden layers of the Deep Q-Network improves the learning process of the agent (4.58 times faster and better) and proves the existence of encoded information about the environment which can be used to select the best action. The research contributes preliminary work in an ongoing research project in modeling features extracted from DRLNs

Undergraduate medical textbooks do not provide adequate information on intravenous fluid therapy: a systematic survey and suggestions for improvement

<b>Background</b><p></p> Inappropriate prescribing of intravenous (IV) fluid, particularly 0.9% sodium chloride, causes post-operative complications. Fluid prescription is often left to junior medical staff and is frequently poorly managed. One reason for poor intravenous fluid prescribing practices could be inadequate coverage of this topic in the textbooks that are used.<p></p> <b>Methods</b><p></p> We formulated a comprehensive set of topics, related to important common clinical situations involving IV fluid therapy, (routine fluid replacement, fluid loss, fluids overload) to assess the adequacy of textbooks in common use. We assessed 29 medical textbooks widely available to students in the UK, scoring the presence of information provided by each book on each of the topics. The scores indicated how fully the topics were considered: not at all, partly, and adequately. No attempt was made to judge the quality of the information, because there is no consensus on these topics.<p></p> <b>Results</b><p></p> The maximum score that a book could achieve was 52. Three of the topics we chose were not considered by any of the books. Discounting these topics as “too esoteric”, the maximum possible score became 46. One textbook gained a score of 45, but the general score was poor (median 11, quartiles 4, 21). In particular, coverage of routine postoperative management was inadequate.<p></p> <b>Conclusions</b><p></p> Textbooks for undergraduates cover the topic of intravenous therapy badly, which may partly explain the poor knowledge and performance of junior doctors in this important field. Systematic revision of current textbooks might improve knowledge and practice by junior doctors. Careful definition of the remit and content of textbooks should be applied more widely to ensure quality and “fitness for purpose”, and avoid omission of vital knowledge

Gas Explosion Venting: External Explosion Turbulent Flame Speeds that Control the Overpressure

In most vented explosions the peak overpressure is controlled by turbulent flame propagation external to the vent. This has been known for many years, but a method to predict the overpressure from the external flame speed has not been developed. Current vent modelling is based on the assumption that the unburned gas flow through the vent controls the overpressure and does not address the issue of the external explosion. This work shows that the external flame speeds in a small vented explosion test facility can be predicted from Taylors’s acoustic theory (1946). Vented explosion data is presented for vent coefficients from 3 – 22 for the most reactive mixtures of methane, propane and ethylene in terms of the overpressure and the external flame speed. The overpressure from Taylors’s acoustic theory give a good prediction of the measured overpressure

Quantitating skill acquisition with optical ultrasound simulation

Objective To investigate and compare the effect of simulator training on quantitative scores for ultrasound‐related skills for trainees with novice level ultrasound experience and expert ultrasound operators. Methods Three novice (comprising of 11, 32, 23 participants) and one expert (10 participants) subgroups undertook an ultrasound simulation training session. Pre‐ and post‐training test scores were collected for each subgroup. Outcome measures were as follows: mean accuracy score for obtaining the correct anatomical plane, percentage of correctly acquired target planes, mean number of movements, time to achieve image, distance travelled by probe and accumulated angling of the probe. Results The novices showed improvement in image acquisition after completion of the simulation training session with an improvement in the rate of correctly acquired target planes from 28–57% to 39–83%. This was not replicated in the experts. The novice’s individual ratios based on pre‐ vs. post‐training metrics improved between 1.7‐ and 4.3‐fold for number of movements, 1.9‐ and 6.7‐fold for distance, 2.0‐ and 5.2‐fold for time taken and 1.8‐ and 7.3‐fold for accumulated angling. Among the experts, there was no relationship between pre‐training simulator metrics and years of ultrasound experience. Conclusions The individual simulation metrics suggest the sessions were delivered at an appropriate level for basic training as novice trainees were able to show demonstrable improvements in both efficiency and accuracy on the simulator. Experts did not improve after the simulation modules, and the novice scores post‐training were similar to those of experts, suggesting the exercises were valid in testing ultrasound skills at novice but not expert level

Evaluating a transfer gradient assumption in a fomite-mediated microbial transmission model using an experimental and Bayesian approach

Current microbial exposure models assume that microbial exchange follows a concentration gradient during hand-to-surface contacts. Our objectives were to evaluate this assumption using transfer efficiency experiments and to evaluate a model's ability to explain concentration changes using approximate Bayesian computation (ABC) on these experimental data. Experiments were conducted with two phages (MS2, ΦX174) simultaneously to study bidirectional transfer. Concentrations on the fingertip and surface were quantified before and after fingertip-to-surface contacts. Prior distributions for surface and fingertip swabbing efficiencies and transfer efficiency were used to estimate concentrations on the fingertip and surface post contact. To inform posterior distributions, Euclidean distances were calculated for predicted detectable concentrations (log10 PFU cm−2) on the fingertip and surface post contact in comparison with experimental values. To demonstrate the usefulness of posterior distributions in calibrated model applications, posterior transfer efficiencies were used to estimate rotavirus infection risks for a fingertip-to-surface and subsequent fingertip-to-mouth contact. Experimental findings supported the transfer gradient assumption. Through ABC, the model explained concentration changes more consistently when concentrations on the fingertip and surface were similar. Future studies evaluating microbial transfer should consider accounting for differing fingertip-to-surface and surface-to-fingertip transfer efficiencies and extend this work for other microbial types

Reconstructing the three-dimensional GABAergic microcircuit of the striatum

A system's wiring constrains its dynamics, yet modelling of neural structures often overlooks the specific networks formed by their neurons. We developed an approach for constructing anatomically realistic networks and reconstructed the GABAergic microcircuit formed by the medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) of the adult rat striatum. We grew dendrite and axon models for these neurons and extracted probabilities for the presence of these neurites as a function of distance from the soma. From these, we found the probabilities of intersection between the neurites of two neurons given their inter-somatic distance, and used these to construct three-dimensional striatal networks. The MSN dendrite models predicted that half of all dendritic spines are within 100 mu m of the soma. The constructed networks predict distributions of gap junctions between FSI dendrites, synaptic contacts between MSNs, and synaptic inputs from FSIs to MSNs that are consistent with current estimates. The models predict that to achieve this, FSIs should be at most 1% of the striatal population. They also show that the striatum is sparsely connected: FSI-MSN and MSN-MSN contacts respectively form 7% and 1.7% of all possible connections. The models predict two striking network properties: the dominant GABAergic input to a MSN arises from neurons with somas at the edge of its dendritic field; and FSIs are interconnected on two different spatial scales: locally by gap junctions and distally by synapses. We show that both properties influence striatal dynamics: the most potent inhibition of a MSN arises from a region of striatum at the edge of its dendritic field; and the combination of local gap junction and distal synaptic networks between FSIs sets a robust input-output regime for the MSN population. Our models thus intimately link striatal micro-anatomy to its dynamics, providing a biologically grounded platform for further study