Quantitative Biology

The aim of this paper is to investigate the cardiorespiratory synchronization in athletes subjected to extreme physical stress combined with a cognitive stress tasks. ECG and respiration were measured in 14 athletes before and after the Ironmen competition. Stroop test was applied between the measurements before and after the Ironmen competition to induce cognitive stress. Synchrogram and empirical mode decomposition analysis were used for the first time to investigate the effects of physical stress, induced by the Ironmen competition, on the phase synchronization of the cardiac and respiratory systems of Ironmen athletes before and after the competition. A cognitive stress task (Stroop test) was performed both pre- and post-Ironman event in order to prevent the athletes from cognitively controlling their breathing rates. Our analysis showed that cardiorespiratory synchronization increased post-Ironman race compared to pre-Ironman. The results suggest that the amount of stress the athletes are recovering from post-competition is greater than the effects of the Stroop test. This indicates that the recovery phase after the competition is more important for restoring and maintaining homeostasis, which could be another reason for stronger synchronization.

Pressure Ulcer is one of the most problems in patients with bed rest. Reposition and skin care are deterrent against the incidence of pressure ulcer. Objective: This study aimed to analyze the effectiveness of sesame oil for the prevention of pressure ulcer in patients with bed rest undergoing hospitalization. Method: This study used a randomized controlled trial design. Forty samples were divided groups: control and intervention groups. This study was analysed using Chi Square. Results: The results showed that there was a significant difference between two group (p=0,04). Conclusions: Skin care with sesame oil can prevention of pressure ulcers. These results recommended that sesame oil can be used for nursing intervention for the prevention of pressure ulcers.

Microbial-Induced Carbonate Precipitation (MICP) has been explored for more than a decade as a promising soil improvement technique. However, it is still challenging to predict and control the growth rate and characteristics of CaCO3 precipitates, which directly affect the engineering performance of MICP-treated soils. In this study, we employ a microfluidics-based pore scale model to observe the effect of bacterial density on the growth rate and characteristics of CaCO3 precipitates during MICP processes occurring at the sand particle scale. Results show that the precipitation rate of CaCO3 increases with bacterial density in the range between 0.6e8 and 5.2e8 cells/ml. Bacterial density also affects both the size and number of CaCO3 crystals. A low bacterial density of 0.6e8 cells/ml produced 1.1e6 crystals/ml with an average crystal volume of 8,000 um3, whereas a high bacterial density of 5.2e8 cells/ml resulted in more crystals (2.0e7 crystals/ml) but with a smaller average crystal volume of 450 um3. The produced CaCO3 crystals were stable when the bacterial density was 0.6e8 cells/ml. When the bacterial density was 4-10 times higher, the crystals were first unstable and then transformed into more stable CaCO3 crystals. This suggests that bacterial density should be an important consideration in the design of MICP protocols.

In Mediterranean aquaculture little research has examined the interaction between rearing density and dietary composition on main key performance indicators, physiological processes and gut bacterial community. A study was undertaken, therefore to assess growth response, digestive enzyme activity, humoral immunity on skin mucus, plasma biochemistry and gut microbiota of gilthead sea bream (Sparus aurata, L. 1758) reared at high (HD) and low (LD) final stocking densities and fed high (FM30FO15, 30 % fishmeal FM, 15 % fish oil, FO) and low (FM10FO3; 10 % FM and 3 % FO) FM and FO levels. Isonitrogenous and isolipidic extruded diets were fed to triplicate fish groups (initial weight: 96.2 g) to overfeeding over 98 days. The densities tested had no major effects on overall growth and feed efficiency of sea bream reared at high or low FM and FO dietary level. Results of digestive enzyme activity indicated a comparable digestive efficiency among rearing densities and within each dietary treatment. Plasma parameters related to nutritional and physiological conditions were not affected by rearing densities under both nutritional conditions a similar observation was also achieved through the study of lysozyme, protease, antiprotease and total protein determination in skin mucus, For the first time on this species, the effect of rearing density on gut bacterial community was studied. Different response in relation to dietary treatment under HD and LD were detected. Low FM-FO diet maintained steady the biodiversity of the gut bacterial community between LD and HD conditions while fish fed high FM-FO level showed a reduced biodiversity at HD. According to the results, it seems feasible to rear gilthead sea bream at the on-growing phase at a density up to 36-44 kg m3 with low or high FM-FO diet without negatively affecting growth, feed efficiency, welfare condition and gut bacterial community.

Limitations in the design of the experiment of Boulware et al[1] are considered in Cohen[2]. They are not subject to correction but they are reported for readers' consideration. However, they made an analysis for the incidence based on Fisher's hypothesis test for means while they published detailed time dependent data which were not analyzed, disregarding an important information. Here we make the analyses with this time dependent data adopting a simple regression analysis. We conclude their randomized, double-blind, placebo-controlled trial presents statistical evidence, at 99% confidence level, that the treatment of Covid-19 patients with hydroxychloroquine is effective in reducing the appearance of symptoms if used before or right after exposure to the virus. For 0 to 2 days after exposure to virus, the estimated relative reduction in symptomatic outcomes is 72% after 0 days, 48.9% after 1 day and 29.3% after 2 days. For 3 days after exposure, the estimated relative reduction is 15.7% but results are not statistically conclusive and for 4 or more days after exposure there is no statistical evidence that hydroxychloroquine is effective in reducing the appearance of symptoms. Our results show that the time elapsed between infection and the beginning of treatment is crucial for the efficacy of hydroxychloroquine as a treatment to Covid-19.

The COVID-19 pandemic has led to an unprecedented response in terms of clinical research activity. An important part of this research has been focused on randomized controlled clinical trials to evaluate potential therapies for COVID-19. The results from this research need to be obtained as rapidly as possible. This presents a number of challenges associated with considerable uncertainty over the natural history of the disease and the number and characteristics of patients affected, and the emergence of new potential therapies. These challenges make adaptive designs for clinical trials a particularly attractive option. Such designs allow a trial to be modified on the basis of interim analysis data or stopped as soon as sufficiently strong evidence has been observed to answer the research question, without compromising the trial's scientific validity or integrity. In this paper we describe some of the adaptive design approaches that are available and discuss particular issues and challenges associated with their use in the pandemic setting. Our discussion is illustrated by details of four ongoing COVID-19 trials that have used adaptive designs.

Performing uncertainty quantification (UQ) and sensitivity analysis (SA) is vital when developing a patient-specific physiological model because it can quantify model output uncertainty and estimate the effect of each of the model's input parameters on the mathematical model. By providing this information, UQ and SA act as diagnostic tools to evaluate model fidelity and compare model characteristics with expert knowledge and real world observation. Computational efficiency is an important part of UQ and SA methods and thus optimization is an active area of research. In this work, we investigate a new efficient sampling method for least-squares polynomial approximation, weighted approximate Fekete points (WAFP). We analyze the performance of this method by demonstrating its utility in stochastic analysis of a cardiovascular model that estimates changes in oxyhemoglobin saturation response. Polynomial chaos (PC) expansion using WAFP produced results similar to the more standard Monte Carlo in quantifying uncertainty and identifying the most influential model inputs (including input interactions) when modeling oxyhemoglobin saturation, PC expansion using WAFP was far more efficient. These findings show the usefulness of using WAFP based PC expansion to quantify uncertainty and analyze sensitivity of a oxyhemoglobin dissociation response model. Applying these techniques could help analyze the fidelity of other relevant models in preparation for clinical application.

Stochastic simulation algorithms (SSAs) are widely used to numerically investigate the properties of stochastic, discrete-state models. The Gillespie Direct Method is the pre-eminent SSA, and is widely used to generate sample paths of so-called agent-based or individual-based models. However, the simplicity of the Gillespie Direct Method often renders it impractical where large-scale models are to be analysed in detail. In this work, we carefully modify the Gillespie Direct Method so that it uses a customised binary decision tree to trace out sample paths of the model of interest. We show that a decision tree can be constructed to exploit the specific features of the chosen model. Specifically, the events that underpin the model are placed in carefully-chosen leaves of the decision tree in order to minimise the work required to keep the tree up-to-date. The computational efficencies that we realise can provide the apparatus necessary for the investigation of large-scale, discrete-state models that would otherwise be intractable. Two case studies are presented to demonstrate the efficiency of the method.

Genetic circuits need a cellular environment to operate in, which naturally couples the circuit function with the overall functionality of gene regulatory network. To execute their functions all gene circuits draw resources in the form of RNA polymerases, ribosomes, and tRNAs. Recent experiments pointed out that the role of resource competition on synthetic circuit outputs could be immense. However, the effect of complexity of the circuit architecture on resource sharing dynamics is yet unexplored. In this paper, we employ mathematical modelling and in-silico experiments to identify the sources of resource trade-off and to quantify its impact on the function of a genetic circuit, keeping our focus on regulation of immediate downstream proteins. We take the example of the fluorescent reporters, which are often used as protein read-outs. We show that estimating gene expression dynamics from readings of downstream protein data might be unreliable when the resource is limited and ribosome affinities are asymmetric. We focus on the impact of mRNA copy number and RBS strength on the nonlinear isocline that emerges with two regimes, prominently separated by a tipping point, and study how correlation and competition dominate each other depending on various circuit parameters. Focusing further on genetic toggle circuit, we have identified major effects of resource competition in this model motif, and quantified the observations. The observations are testable in wet-lab experiments, as all the parameters chosen are experimentally relevant.

We present experimental results demonstrating that, relative to continuous illumination, an increase of a factor of 3-10 in the photon efficiency of algal photo-synthesis is attainable via the judicious application of pulsed light for light intensities of practical interest (e.g., average-to-peak solar photon flux). We also propose a simple model that can account for all the measurements. The model (1) reflects the essential rate-limiting elements in bio-productivity, (2) incorporates the impact of photon arrival-time statistics and (3) accounts for how the enhancement in photon efficiency depends on the timescales of light pulsing and photon flux density. The key is avoiding clogging of the photosynthetic pathway by properly timing the light-dark cycles experienced by algal cells. We show how this can be realized with pulsed light sources, or by producing pulsed-light effects from continuous illumination via turbulent mixing in dense algal cultures in thin photo-bioreactors.