High Bubble Grade After Diving: The Role of the Blood Pressure Regimen

Boussuges, Alain; Chaumet, Guillaume; Vallée, Nicolas; Risso, Jean-Jacques; Pontier, Jean-Michel

doi:10.3389/fphys.2019.00749

Cited by 3 publications

(2 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…More recently 34 , applied MMPC in order to identify the features that provide novel information about steady-state plasma glucose (SSPG, a measure of peripheral insulin resistance) and are thus most useful for prediction 35 . used gOMP and identified the viscoelastic properties of the arterial tree as an important contributor to the circulating bubble production after a dive.…”

Section: Use Casesmentioning

confidence: 99%

Feature selection with the R package MXM

Tsagris

Tsamardinos

2019

F1000Res

View full text Add to dashboard Cite

Feature (or variable) selection is the process of identifying the minimal set of features with the highest predictive performance on the target variable of interest. Numerous feature selection algorithms have been developed over the years, but only few have been implemented in R and made publicly available R as packages while offering few options. The R package MXM offers a variety of feature selection algorithms, and has unique features that make it advantageous over its competitors: a) it contains feature selection algorithms that can treat numerous types of target variables, including continuous, percentages, time to event (survival), binary, nominal, ordinal, clustered, counts, left censored, etc; b) it contains a variety of regression models that can be plugged into the feature selection algorithms (for example with time to event data the user can choose among Cox, Weibull, log logistic or exponential regression); c) it includes an algorithm for detecting multiple solutions (many sets of statistically equivalent features, plain speaking, two features can carry statistically equivalent information when substituting one with the other does not effect the inference or the conclusions); and d) it includes memory efficient algorithms for high volume data, data that cannot be loaded into R (In a 16GB RAM terminal for example, R cannot directly load data of 16GB size. By utilizing the proper package, we load the data and then perform feature selection.). In this paper, we qualitatively compare MXM with other relevant feature selection packages and discuss its advantages and disadvantages. Further, we provide a demonstration of MXM’s algorithms using real high-dimensional data from various applications.

show abstract

Section: Use Casesmentioning

confidence: 99%

Feature selection with the R package MXM

Tsagris

Tsamardinos

2019

F1000Res

View full text Add to dashboard Cite

show abstract

“…31 It is estimated 32 that at least 70% of occupational sea divers experienced decompression sickness and that this incidence is even higher in low-income and middle-income countries. Furthermore, decompression sickness is presently an underestimated professional hazard for aquaculturists and deep-sea divers, 33 as climate change forces deeper diving. 34 Presently, the morbidity and mortality of gas embolism cannot be completely quantified due to the complexity of reported cases, possibly coupled with underreporting.…”

Section: Introductionmentioning

confidence: 99%

<em></em> <i>In Vitro</i> Investigation of Gas Embolism in Microfluidic Networks Mimicking Microvasculature

Mardanpour¹,

Perumal²,

Mahmoodi³

et al. 2022

Preprint

View full text Add to dashboard Cite

Gas embolism is a medical condition leading to the blockage of blood flow in the microvasculature by gas bubbles. While reported as rare, gas embolism often has devastating, fatal physiological consequences. Despite this acute importance, the genesis and evolution of air bubbles in blood vessels under different physiological conditions, such as blood viscosity and blood flow rate, is still understudied, largely because of difficult experimentation and in situ visualization. The objective of this work was to study the gas embolism phenomenon in vitro, using a microfluidic system that mimicked the architecture of microvasculature. The microfluidic systems comprised linear channels with two different air inlet types, namely, T- and Y-junctions with three different widths (20 µm, 40 µm, and 60 µm), and a 30 µm width honeycombed network with three bifurcation angles (30°, 60°, and 90°). Three synthetic liquids equivalent to 0%, 20%, and 46% hematocrit that mimicked the physiological blood viscosity and hematocrit concentrations were used. Our results show that: (i) 20 µm and 40 µm width channels had an elevated risk of gas embolism due to wide fluctuations in the total slug sizes; (ii) the resistance to the flow of air bubbles increased with the increase in the equivalent concentration of hematocrit; (iii) gas bubbles causing blockages and dampening of the flow velocity were frequently observed in 20 µm channels, and lastly (iv) increased risk of gas embolism was observed in the honeycomb architecture with 60° and 30° bifurcations. This work suggests that in vitro experimentation using microfluidic devices with microvascular tissue-like structures opens the possibility of studying this medical condition with high reproducibility and impacts the fact-based medical guidelines for preventing or mitigating iatrogenic occurrences.

show abstract

Blood pressure in rats selectively bred for their resistance to decompression sickness

Dugrenot¹,

Orsat²,

Guerrero³

2022

Diving Hyperb Med

View full text Add to dashboard Cite

Introduction: Susceptibility to decompression sickness (DCS) is characterised by a wide inter-individual variability whose origins are still poorly understood. This hampers reliable prediction of DCS by decompression algorithms. We previously selectively bred rats with a 3-fold greater resistance to DCS than standard rats. Based on its previously reported relation with decompression outcomes, we assessed whether modification in vascular function is associated with resistance to DCS. Methods: The arterial pressure response to intravenous administration of acetylcholine (ACh, 5 µg.kg-1) and adrenaline (5 and 10 µg.kg-1) was compared in anaesthetised DCS-resistant rats (seven females, seven males) and standard Wistar rats (seven females, 10 males) aged 14-15 weeks. None of these rats had previously undergone hyperbaric exposure. Results: There was a non-significant tendency for a lower diastolic (DBP) and mean blood pressure (MBP) in DCS-resistant rats. After ACh administration, MBP was significantly lower in resistant rats, for both males (P = 0.007) and females (P = 0.034). After administration of adrenaline 10 µg.kg-1, DCS-resistant rats exhibited lower maximal DBP (P = 0.016) and MBP (P = 0.038). Systolic and pulse blood pressure changes did not differ between groups in any of the experiments. Conclusions: Resistance to DCS in rats is associated to a trend towards a lower vascular tone but not blood pressure reactivity. Whether these differences are a component of the susceptibility to DCS remains to be confirmed.

show abstract

High Bubble Grade After Diving: The Role of the Blood Pressure Regimen

Cited by 3 publications

References 41 publications

Feature selection with the R package MXM

Feature selection with the R package MXM

<em></em> <i>In Vitro</i> Investigation of Gas Embolism in Microfluidic Networks Mimicking Microvasculature

Blood pressure in rats selectively bred for their resistance to decompression sickness

Contact Info

Product

Resources

About