Reproductive biology of female blue shark <Emphasis Type="Italic">Prionace glauca</Emphasis> in the southeastern Pacific Ocean

Polyandry is extremely common across a wide range of organisms. In promiscuous mating systems, females are often sexually harassed by males, but at the same time obtain benefits from multiple mating. It remains unclear whether polyandry is exclusively imposed by males or is also promoted by females. Here, we investigated this question by recording the time spent by female guppies near a single male or a group of males with similar size and colour patterns over three consecutive days. We accounted for the effect of shoaling by using a control treatment where a group of females was used instead of a group of males. Results showed that females spent significantly more time near the group of males, but not with the group of females. In the presence of a group of males, total female mating preference time did not change over the course of the study, but rather shifted from spending more time near the single male at the beginning of the experiment to spending more time near the group of males. The consequence of this female preference for associating with a group of males in a non-experimental setup would be to promote multiple mating. Our result indicates that polyandry in guppies is at least partially encouraged by females, and not entirely a consequence of male sexual behaviour.     

A network model of early events in epidermal growth factor receptor signaling that accounts for combinatorial complexity

We consider a model of early events in signaling by the epidermal growth factor (EGF) receptor (EGFR). The model includes EGF, EGFR, the adapter proteins Grb2 and Shc, and the guanine nucleotide exchange factor Sos, which is activated through EGF-induced formation of EGFR-Grb2-Sos and EGFR-Shc-Grb2-Sos assemblies at the plasma membrane. The protein interactions involved in signaling can potentially generate a diversity of protein complexes and phosphoforms; however, this diversity has been largely ignored in models of EGFR signaling. Here, we develop a model that accounts more fully for potential molecular diversity by specifying rules for protein interactions and then using these rules to generate a reaction network that includes all chemical species and reactions implied by the protein interactions. We obtain a model that predicts the dynamics of 356 molecular species, which are connected through 3749 unidirectional reactions. This network model is compared with a previously developed model that includes only 18 chemical species but incorporates the same scope of protein interactions. The predictions of this model are reproduced by the network model, which also yields new predictions. For example, the network model predicts distinct temporal patterns of autophosphorylation for different tyrosine residues of EGFR. A comparison of the two models suggests experiments that could lead to mechanistic insights about competition among adapter proteins for EGFR binding sites and the role of EGFR monomers in signal transduction.     

A halotolerant and thermotolerant <Emphasis Type="Italic">Bacillus</Emphasis> sp. degrades hydrocarbons and produces tensio-active emulsifying agent

A Bacillus sp. strain DHT, isolated from oil-contaminated soil, grew and produced biosurfactant when cultured in variety of substrate at salinities of up to 100 g l⁻¹ and temperatures up to 45°C. It was capable of utilizing crude oil, fuels, various pure alkanes and PAHs as a sole carbon and energy source across a wide range of temperature and salinity. Over the range evaluated, the degradation of hydrocarbon and biosurfactant production was not influenced by salinity (0–10% wv⁻¹) and temperature (30–45°C). The biosurfactant produced by the organism emulsified a range of hydrocarbons with hexadecane as the best substrate and toluene as the poorest. From 16S rDNA analysis, strain DHT was related to Bacillus licheniformis.     

Algorithms for matching partially labelled sequence graphs

Background

In order to find correlated pairs of positions between proteins, which are useful in predicting interactions, it is necessary to concatenate two large multiple sequence alignments such that the sequences that are joined together belong to those that interact in their species of origin. When each protein is unique then the species name is sufficient to guide this match, however, when there are multiple related sequences (paralogs) in each species then the pairing is more difficult. In bacteria a good guide can be gained from genome co-location as interacting proteins tend to be in a common operon but in eukaryotes this simple principle is not sufficient.

Results

The methods developed in this paper take sets of paralogs for different proteins found in the same species and make a pairing based on their evolutionary distance relative to a set of other proteins that are unique and so have a known relationship (singletons). The former constitute a set of unlabelled nodes in a graph while the latter are labelled. Two variants were tested, one based on a phylogenetic tree of the sequences (the topology-based method) and a simpler, faster variant based only on the inter-sequence distances (the distance-based method). Over a set of test proteins, both gave good results, with the topology method performing slightly better.

Conclusions

The methods develop here still need refinement and augmentation from constraints other than the sequence data alone, such as known interactions from annotation and databases, or non-trivial relationships in genome location. With the ever growing numbers of eukaryotic genomes, it is hoped that the methods described here will open a route to the use of these data equal to the current success attained with bacterial sequences.

     

Patient and observer reported outcome measures to evaluate health-related quality of life in inherited metabolic diseases: a scoping review

Background

Health-related Quality of Life (HrQoL) is a multidimensional measure, which has gained clinical and social relevance. Implementation of a patient-centred approach to both clinical research and care settings, has increased the recognition of patient and/or observer reported outcome measures (PROMs or ObsROMs) as informative and reliable tools for HrQoL assessment. Inherited Metabolic Diseases (IMDs) are a group of heterogeneous conditions with phenotypes ranging from mild to severe and mostly lacking effective therapies. Consequently, HrQoL evaluation is particularly relevant.

Objectives

We aimed to: (1) identify patient and/or caregiver-reported HrQoL instruments used among IMDs; (2) identify the main results of the application of each HrQoL tool and (3) evaluate the main limitations of HrQoL instruments and study design/methodology in IMDs.

Methods

A scoping review was conducted using methods outlined by Arksey and O’Malley. Additionally, we critically analysed each article to identify the HrQoL study drawbacks.

Results

Of the 1954 studies identified, 131 addressed HrQoL of IMDs patients using PROMs and/or ObsROMs, both in observational or interventional studies. In total, we identified 32 HrQoL instruments destined to self- or proxy-completion; only 2% were disease-specific. Multiple tools (both generic and disease-specific) proved to be responsive to changes in HrQoL; the SF-36 and PedsQL questionnaires were the most frequently used in the adult and pediatric populations, respectively. Furthermore, proxy data often demonstrated to be a reliable approach complementing self-reported HrQoL scores. Nevertheless, numerous limitations were identified especially due to the rarity of these conditions.

Conclusions

HrQoL is still not frequently assessed in IMDs. However, our results show successful examples of the use of patient-reported HrQoL instruments in this field. The importance of HrQoL measurement for clinical research and therapy development, incites to further research in HrQoL PROMs’ and ObsROMs’ creation and validation in IMDs.

     

Morpho-physiology and maize grain yield under periodic soil flooding in successive selection cycles

This study was carried out to evaluate maize plants of different recurrent selection cycles of the variety (Zea mays L.—Saracura-BRS-4154) regarded to genetic gains, morphophysiology, and grain yield, achieved over the selection cycles under intermittent flooding of the soil. This variety has the capacity to survive and produce in temporarily flooded soils and was developed by the National Maize and Sorghum Research Center (EMBRAPA). The experiment was conducted in greenhouse by using ten alternating selection cycles (Cycle 1–18) and BR 107 a variety known for its susceptibility to flooding. The flooding initiated at six-leaf stage by applying 50 mm of water three times a week. At flowering, the following parameters were evaluated: rate of leaf photosynthesis, stomatal conductance, intercellular CO₂ concentration, transpiration rate, photosynthetically active leaf area, root porosity, relative chlorophyll content, grain yield, harvest index, ear length, and interval between male and female flowering. Yield as a function of root porosity and photosynthesis were also evaluated. An index was created in this study, in order to help the discussion of the characteristics evaluated, it was called “Relative Tolerance Value—RTV”, only gaseous exchange measurements was not included in this index. By the way, it was observed throughout the selection cycles an increase in all gaseous exchange parameters, being the cycle 18, the one which presented the greatest averages. RTV for leaf area showed the greatest values for cycles 7 and 18, whereas root porosity, chlorophyll relative content, and harvest index, the greater RTV values were found in cycles 17 and 18. The largest grain yield RTV was observed in cycle 7, followed by cycles 13, 15, and 18. Flooding resulted in longer Anthesis-Silking Interval, especially for the first cycles. At flooding condition, grain yield was strongly related to root porosity (R ² = 0.66). These results showed that the selection cycles of “Saracura” maize improved some morphophysiologic characters, which favor their survival in flooded environments, also resulting in higher productivity.     

Strain-induced inflammation in pulmonary alveolar tissue due to mechanical ventilation

Inflammation is the body’s attempt at self-protection to remove harmful stimuli, including damaged cells, irritants, or pathogens and begin the healing process. In this study, strain-induced inflammation in pulmonary alveolar tissue under high tidal volume is investigated through a combination of an inflammation model and fluid structure interaction (FSI) analysis. A realistic three-dimensional organ model for alveolar sacs is built, and FSI is employed to evaluate strain distribution in alveolar tissue for different tidal volume (TV) values under the mechanical ventilation (MV) condition. The alveolar tissue is treated as a hyperelastic solid and provides the environment for the tissue constituents. The influence of different strain distributions resulting from different tidal volumes is investigated. It is observed that strain is highly distributed in the inlet area. In addition, strain versus time curves in different locations through the alveolar model reveals that middle layers in the alveolar region would undergo higher levels of strain during breathing under the MV condition. Three different types of strain distributions in the alveolar region from the FSI simulation are transferred to the CA model to study population dynamics of cell constituents under MV for different TVs; 200, 500 and 1000 mL, respectively. The CA model results suggests that strain distribution plays a significant role in population dynamics. An interplay between strain magnitude and distribution appears to influence healing capability. Results suggest that increasing TV leads to an exponential rise in tissue damage by inflammation.