Facial symmetry detection ability changes across the menstrual cycle

The effects of menstrual cycle phase and hormones on women's visual ability to detect symmetry and visual preference for symmetry were examined. Participants completed tests of symmetry detection and preference for male facial symmetry at two of three menstrual cycle phases (menses, periovulatory, and luteal). Women were better at detecting facial symmetry during the menses than luteal phase of their cycle. A trend indicated the opposite pattern for dot symmetry detection. Similarly, change in salivary progesterone levels across the cycle was negatively related to change in facial symmetry detection scores. However, there was no clear evidence of a greater preference for facial symmetry at any cycle phase, despite an overall preference for facial symmetry across phases. These findings suggest a menses phase advantage and a low progesterone advantage in women's ability to detect facial symmetry. The results are discussed in the context of hormonal, evolutionary mate selection, and functional neurocognitive theories.     

Preferences for symmetry in faces change across the menstrual cycle

Symmetry in human male faces may be a cue to heritable fitness benefits and is found attractive. Preferences for facial masculinity, another proposed marker of genetic quality, have been found to vary in ways that may maximise evolutionary relevant benefits and masculinity is found to be of increased attractiveness at peak fertility across the menstrual cycle. Here we show that women prefer more symmetric faces at peak fertility (Study 1) and that such shifting preferences may be potentially strategic preferences as we found them to occur only for judgements concerning short-term relations and when women already had a partner (Study 2). Such preferences potentially indicate a strategy that maximises the quality of extra-pair/short-term partners or a quality dependent response to hormones. Such strategic preferences for symmetry may support the role of symmetry in signalling potential good-gene benefits.     

Mucoadhesive chitosan-coated nanostructured lipid carriers for oral delivery of amphotericin B

This study describes the properties of an amphotericin B-containing mucoadhesive nanostructured lipid carrier (NLC), with the intent to maximize uptake within the gastrointestinal tract. We have reported previously that lipid nanoparticles can significantly improve the oral bioavailability of amphotericin B (AmpB). On the other hand, the aggregation state of AmpB within the NLC has been ascribed to some of the side effects resulting from IV administration. In the undissolved state, AmpB (UAmpB) exhibited the safer monomeric conformation in contrast to AmpB in the dissolved state (DAmpB), which was aggregated. Chitosan-coated NLC (ChiAmpB NLC) presented a slightly slower AmpB release profile as compared to the uncoated formulation, achieving 26.1% release in 5?hours. Furthermore, the ChiAmpB NLC formulation appeared to prevent the expulsion of AmpB upon exposure to simulated gastrointestinal pH media, whereby up to 63.9% of AmpB was retained in the NLC compared to 56.1% in the uncoated formulation. The ChiAmpB NLC demonstrated mucoadhesive properties in pH 5.8 and 6.8. Thus, the ChiAmpB NLC formulation is well-primed for pharmacokinetic studies to investigate whether delayed gastrointestinal transit may be exploited to improve the systemic bioavailability of AmpB, whilst simultaneously addressing the side-effect concerns of AmpB.     

Comparison of some intrinsic risk factors of shoulder injury in three phases of menstrual cycle in collegiate female athletes

Objectivespresent study aims to investigate the changes in the shoulder joint stability factors during the menstrual cycle.Designcross-sectional study;Settinglaboratory.Participants15 healthy collegiate female athletes with normal menstrual cycles.Main outcome measuresshoulder strength, proprioception, laxity and functional stability were the primary outcomes. Participants were assessed in three phases (mense, ovulation, midluteal (day 21) by 4 different categories of tests, each designed for a different factor. Shapiro-Wilk Test was used to determine normality of data, ANOVA and Friedman Test were used to compare results. Significance level and alpha were considered 95 percent and ≥0.05, respectively. Data shown a relation between proprioception, strength and menstrual cycle.Resultsshoulder strength was significantly increased in ovulation phase compared to other phases (p < 0.5) (effect size >0.14). Proprioception was significantly decreased in luteal phase than in mense and ovulation phases (p < 0.5) (effect size >0.14). Finally, ligament laxity and functional stability showed no change in all phases (p < 0.5).ConclusionMenstrual cycle and sexual hormones affect muscle strength and proprioception of shoulder joint, but have no effect on ligament laxity and functional stability.     

What is microglia neurotoxicity (Not)?

Microglia most likely appeared early in evolution as they are not only present in vertebrates, but are also found in nervous systems of various nonvertebrate organisms. Mammalian microglia are derived from a specific embryonic, self‐renewable myeloid cell population that is throughout lifetime not replaced by peripheral myeloid cells. These phylogenic and ontogenic features suggest that microglia serve vital functions. Yet, microglia often are described as neurotoxic cells, that actively kill (healthy) neurons. Since it is from an evolutionary point of view difficult to understand why an important and vulnerable organ like the brain should host numerous potential killers, we here review the concept of microglia neurotoxicity. On one hand it is discussed that most of our understanding about how microglia kill neurons is based on in vitro experiments or correlative staining studies that suffer from the difficulty to discriminate microglia and peripheral myeloid cells in the diseased brain. On the other hand it is described that a more functional approach by mutating, inactivating or deleting microglia is seldom associated with a beneficial outcome in an acute injury situation, suggesting that microglia are normally important protective elements in the brain. This might change in chronic disease or the aged brain, where; however, it remains to be established whether microglia simply lose their protective capacities or whether microglia become truly neurotoxic cells. GLIA 2014;62:841–854     

States of Water in Hydrogels Containing with Glyceryl Methacrylate

Hydrogel materials were prepared by thermopolymerization with different content of glyceryl methacrylate and hydroxyethyl methacrylate. The different states of water in swelling hydrogels were described and studied by differential scanning calorimetry （DSC）. It was found that the hydrophilicity of GMA was stronger than HEMA, the water content and bound water of GMA hydrogel are higher than HEMA hydrogel. With the increase of GMA content, the content of free water in hydrogel increased. When GMA content was lower than 50%, the increase of GMA content also increased the content of bound water; but when GMA content was higher than 50%, the increase of GMA content decreased the content of bound water, which was caused by the chain hydrogen bond formed on the GMA chain with hydroxyl group each other.     

Spatiotemporal analysis of event‐related fMRI to reveal cognitive states

Cognitive science has a rich history of developing theories of processing that characterize the mental steps involved in performance of many tasks. Recent work in neuroimaging and machine learning has greatly improved our ability to link cognitive processes with what is happening in the brain. This article analyzes a hidden semi‐Markov model‐multivoxel pattern‐analysis (HSMM‐MVPA) methodology that we have developed for inferring the sequence of brain states one traverses in the performance of a cognitive task. The method is applied to a functional magnetic resonance imaging (fMRI) experiment where task boundaries are known that should separate states. The method is able to accurately identify those boundaries. Then, applying the method to synthetic data, we explore more fully those factors that influence performance of the method: signal‐to‐noise ratio, numbers of states, state sojourn times, and numbers of underlying experimental conditions. The results indicate the types of experimental tasks where applications of the HSMM‐MVPA method are likely to yield accurate and insightful results.     

Unveiling whole‐brain dynamics in normal aging through Hidden Markov Models

During normal aging, the brain undergoes structural and functional changes. Many studies applied static functional connectivity (FC) analysis on resting state functional magnetic resonance imaging (rs‐fMRI) data showing a link between aging and the increase of between‐networks connectivity. However, it has been demonstrated that FC is not static but varies over time. By employing the dynamic data‐driven approach of Hidden Markov Models, this study aims to investigate how aging is related to specific characteristics of dynamic brain states. Rs‐fMRI data of 88 subjects, equally distributed in young and old were analyzed. The best model resulted to be with six states, which we characterized not only in terms of FC and mean BOLD activation, but also uncertainty of the estimates. We found two states were mostly occupied by young subjects, whereas three other states by old subjects. A graph‐based analysis revealed a decrease in strength with the increase of age, and an overall more integrated topology of states occupied by old subjects. Indeed, while young subjects tend to cycle in a loop of states characterized by a high segregation of the networks, old subjects'' loops feature high integration, with a crucial intermediary role played by the dorsal attention network. These results suggest that the employed mathematical approach captures the complex and rich brain''s dynamics underpinning the aging process.