How does gene expression clustering work?

Clustering is often one of the first steps in gene expression analysis. How do clustering algorithms work, which ones should we use and what can we expect from them?     

How does a legume nodule work?

Nitrogen fixation in legume root nodules requires biochemical cooperation between the plant and Rhizobium cells. Bacteroids contribute the N₂-fixing system and haem for leghaemoglobin, but apart from the production of the globin moiety of leghaemoglobin and the assimilation and export of the NH₃ produced, little is known about the contributions of the plant. It now appears that the plant cell may regulate the type and/or quantity of carbon compounds supplied to the Rhizobium bacteroids.     

Integration of omics data: how well does it work for bacteria?

In the current omics era, innovative high-throughput technologies allow measuring temporal and conditional changes at various cellular levels. Although individual analysis of each of these omics data undoubtedly results into interesting findings, it is only by integrating them that gaining a global insight into cellular behaviour can be aimed at. A systems approach thus is predicated on data integration. However, because of the complexity of biological systems and the specificities of the data-generating technologies (noisiness, heterogeneity, etc.), integrating omics data in an attempt to reconstruct signalling networks is not trivial. Developing its methodologies constitutes a major research challenge. Besides for their intrinsic value towards health care, environment and industry, prokaryotes are ideal model systems to further develop these methods because of their lower regulatory complexity compared with eukaryotes, and the ease with which they can be manipulated. Several successful examples outlined in this review already show the potential of the systems approach for both fundamental and industrial applications, which would be time-consuming or impossible to develop solely through traditional reductionist approaches.     

How does infliximab work in rheumatoid arthritis?

Since the initial characterization of tumor necrosis factor alpha (TNFalpha), it has become clear that TNFalpha has diverse biologic activity. The realization that TNFalpha plays a role in rheumatoid arthritis (RA) has led to the development of anti-TNF agents for the treatment of RA. Infliximab, a chimeric monoclonal antibody that specifically, and with high affinity, binds to TNFalpha and neutralizes the cytokine, is currently approved for the treatment of RA and Crohn's disease, another immune-inflammatory disorder. In addition to establishing the safety and efficacy of infliximab, clinical research has also provided insights into the complex cellular and cytokine-dependent pathways involved in the pathophysiology of RA, including evidence that supports TNFalpha involvement in cytokine regulation, cell recruitment, angiogenesis, and tissue destruction.     

Sperm storage in the vertebrate female reproductive tract: How does it work so well?

The capacity for sperm storage within the female reproductive tract occurs widely across all groups of vertebrate species and is exceptionally well developed in some reptiles (maximum duration, 7 yr) and fish (maximum duration, >1 yr). Amphibians (most salamanders and one species of frog; duration approximately 5 mo), all birds examined to date and some bats, have also evolved the ability to store spermatozoa in the female reproductive tract. Although there are many reports on both the occurrence of female sperm storage and its adaptive benefits, few studies have been directed toward explaining the mechanisms involved. Phylogenetic evidence suggests that the capacity for sperm storage has evolved independently within different taxonomic groups, and it is by no means clear whether these groups have established similar or different mechanisms or whether simple and common principles have been exploited during evolution. If the process has indeed developed by the invention of numerous different and species-specific mechanisms, it is surprising that none have yet been elucidated by technologists wishing to improve the long-term storage of fresh semen. On the other hand, if there is a simple and common solution to the problem, readily accessed by diverse groups of species, it is equally logical to suppose that the mechanism should be easily discovered in the laboratory. While recognizing that studies on wild species are usually neither practically or ethically easy to undertake, it is clear that there is a huge and largely unexplored field to be investigated.     

How does HIV cause AIDS? The homing theory

The mechanism by which HIV causes depletion of CD4+ T cells in infected individuals remains unknown. Numerous theories have been proposed, but none can fully explain all of the events observed to occur in patients. Recent studies have shown that HIV binding to resting CD4+ T cells upregulates L-selectin, causing the cells to home from the blood into lymph nodes at an enhanced rate. It is possible that the disappearance of CD4+ T cells in the blood is actually the result of them leaving the blood, which can help explain the loss of CD4+ T cells in the blood occurring at a much faster rate than in lymphoid tissues. Furthermore, secondary signals through homing receptors received during the homing process induce many of these cells into apoptosis. These cells die in the lymph nodes without producing HIV particles, which can explain the 'bystander effect' observed in the lymph nodes of HIV infected individuals. If this scenario occurs in HIV+ patients, it might explain many of the clinical observations.     

How well does the HoT score reflect sequence alignment accuracy?

Multiple sequence alignment is an essential tool in many areas of biological research, and the accuracy of an alignment can strongly affect the accuracy of a downstream application such as phylogenetic analysis, identification of functional motifs, or polymerase chain reaction primer design. The heads or tails (HoT) method (Landan G, Graur D. 2007. Heads or tails: a simple reliability check for multiple sequence alignments. Mol Biol Evol. 24:1380-1383.) assesses the consistency of an alignment by comparing the alignment of a set of sequences with the alignment of the same set of sequences written in reverse order. This study shows that HoT scores and the alignment accuracies are positively correlated, so alignments with higher HoT scores are preferable. However, HoT scores are overestimates of alignment accuracy in general, with the extent of overestimation depending on the method used for multiple sequence alignment.     

How well do mean field theories of spiking quadratic-integrate-and-fire networks work in realistic parameter regimes?

We use mean field techniques to compute the distribution of excitatory and inhibitory firing rates in large networks of randomly connected spiking quadratic integrate and fire neurons. These techniques are based on the assumption that activity is asynchronous and Poisson. For most parameter settings these assumptions are strongly violated; nevertheless, so long as the networks are not too synchronous, we find good agreement between mean field prediction and network simulations. Thus, much of the intuition developed for randomly connected networks in the asynchronous regime applies to mildly synchronous networks.     

Smith‐Lemli‐Opitz syndrome in trisomy 13: How does the mix work?

BACKGROUND: Trisomy 13 and Smith-Lemli-Opitz syndrome (SLOS) are both well-recognized multiple congenital anomaly/mental retardation syndromes. CASE: In this report we describe a male newborn with trisomy 13 who also has features of SLOS, such as 2/3 toe syndactyly and a shawl-like scrotum. Biochemical analysis was consistent with SLOS, and limited molecular analysis revealed 1 mutation in the DHCR7 gene. CONCLUSIONS: The challenges in establishing the diagnosis of SLOS in this patient are presented and the unique coexistence of the 2 major malformation syndromes is discussed. Given the overlapping phenotype of the 2 syndromes, our report should encourage further research on cholesterol biosynthesis in patients with trisomy 13.     

Modulating social behavior with oxytocin: How does it work? What does it mean?

Among its many roles in body and brain, oxytocin influences social behavior. Understanding the precise nature of this influence is crucial, both within the broader theoretical context of neurobiology, social neuroscience and brain evolution, but also within a clinical context of disorders such as anxiety, schizophrenia, and autism. Research exploring oxytocin's role in human social behavior is difficult owing to its release in both body and brain and its interactive effects with other hormones and neuromodulators. Additional difficulties are due to the intricacies of the blood-brain barrier and oxytocin's instability, which creates measurement issues. Questions concerning how to interpret behavioral results of human experiments manipulating oxytocin are thus made all the more pressing. The current paper discusses several such questions. We highlight unresolved fundamental issues about what exactly happens when oxytocin is administered intranasally, whether such oxytocin does in fact reach appropriate receptors in brain, and whether central or peripheral influences account for the observed behavioral effects. We also highlight the deeper conceptual issue of whether the human data should be narrowly interpreted as implicating a specific role for oxytocin in complex social cognition, such a generosity, trust, or mentalizing, or more broadly interpreted as implicating a lower-level general effect on general states and dispositions, such as anxiety and social motivation. Using several influential studies, we show how seemingly specific, higher-level social-cognitive effects can emerge via a process by which oxytocin's broad influence is channeled into a specific social behavior in a context of an appropriate social and research setting. This article is part of a Special Issue entitled Oxytocin, Vasopressin, and Social Behavior.     

How well does cholesteryl hemisuccinate mimic cholesterol in saturated phospholipid bilayers?

Journal of Molecular Modeling - We studied the doping effects on the electronic and structural properties of graphene upon interaction with phenol. Calculations were performed within the periodic...     

How well does presence‐only‐based species distribution modelling predict assemblage diversity? A case study of the Tenerife flora

Prediction error is considered an important problem in species distribution models. To address this issue, we here examined the accuracy of overlays of presence‐only‐based models for many individual species in representing patterns of assemblage diversity. For this purpose, we used a database of 977 160 records of seed plant occurrences on an intensively surveyed, species‐rich island (Tenerife, Canary Islands) for modelling the distribution of all its 841 native plant species individually. The modelling was done using Maxent, one of the best‐performing presence‐only modelling techniques, using various thresholds to convert the estimated suitability values into predicted presence or absence. Distribution models for each individual species were overlaid to predict species richness and composition, which were then compared to the observed values for well‐surveyed grid cells. We found high levels of compositional error, when the best performing suitability threshold for predicting species richness was applied. Our best prediction had a mean species richness error of 24% and a mean compositional error of 60% relative to the observed values for the well‐surveyed cells; >50% of all species were included erroneously in >25% of the well‐surveyed cells. Hence, large quantities of data are not necessarily enough to obtain reliable predictions of assemblage diversity, limiting the usefulness of this methodology in conservation planning.     

How does the reliability of a model affect children's choice to learn socially or individually?

The effect of model reliability on children's choices to learn socially versus individually is pertinent to theories addressing cultural evolution and theories of selective trust. Here the effect of a reliable versus unreliable model on children's preferences to learn socially or individually was examined, as well as their subsequent imitation on a puzzle box task. Experiment One (N = 156) found children were more likely to ask to learn socially when presented with a novel task, after witnessing an unreliable rather than a reliable model. Experiment Two (N = 40) found children select a new unknown model, over the previously unreliable model, suggesting a preference to learn socially was created, although not specifically from the unreliable model. Experiment Three (N = 48) replicated children's learning preference in Experiment One with a new task, and showed children's attention is drawn towards other sources of social information (another adult model) when viewing an unreliable model, and also found a reliable model caused more fidelity of imitation. Together these results suggest that model unreliability causes greater social learning requests and attention to other, even novel, models when they are available. These findings evidence human children's strong propensity to learn socially compared with non-human animals; and suggest there is a more complicated relationship between learning preference, model reliability and selective trust than has been captured in previous research.     

How well does a commercially available wearable device measure sleep in young athletes?

ABSTRACT

The validity of a commercially available wearable device for measuring total sleep time was examined in a sample of well-trained young athletes during night-time sleep periods and daytime naps. Participants wore a FitBit HR Charge on their non-dominant wrist and had electrodes attached to their face and scalp to enable polysomnographic recordings of sleep in the laboratory. The FitBit automatically detected 24/30 night-time sleep periods but only 6/20 daytime naps. Compared with polysomnography, the FitBit overestimated total sleep time by an average of 52 ± 152 min for night-time sleep periods, and by 4 ± 8 min for daytime naps. It is important for athletes and practitioners to be aware of the limitations of wearable devices that automatically detect sleep duration.