Postcopulatory sexual selection

The female reproductive tract is where competition between the sperm of different males takes place, aided and abetted by the female herself. Intense postcopulatory sexual selection fosters inter-sexual conflict and drives rapid evolutionary change to generate a startling diversity of morphological, behavioural and physiological adaptations. We identify three main issues that should be resolved to advance our understanding of postcopulatory sexual selection. We need to determine the genetic basis of different male fertility traits and female traits that mediate sperm selection; identify the genes or genomic regions that control these traits; and establish the coevolutionary trajectory of sexes

Combinatorial Roles of Heparan Sulfate Proteoglycans and Heparan Sulfates in Caenorhabditis elegans Neural Development

Heparan sulfate proteoglycans (HSPGs) play critical roles in the development and adult physiology of all metazoan organisms. Most of the known molecular interactions of HSPGs are attributed to the structurally highly complex heparan sulfate (HS) glycans. However, whether a specific HSPG (such as syndecan) contains HS modifications that differ from another HSPG (such as glypican) has remained largely unresolved. Here, a neural model in C. elegans is used to demonstrate for the first time the relationship between specific HSPGs and HS modifications in a defined biological process in vivo. HSPGs are critical for the migration of hermaphrodite specific neurons (HSNs) as genetic elimination of multiple HSPGs leads to 80% defect of HSN migration. The effects of genetic elimination of HSPGs are additive, suggesting that multiple HSPGs, present in the migrating neuron and in the matrix, act in parallel to support neuron migration. Genetic analyses suggest that syndecan/sdn-1 and HS 6-O-sulfotransferase, hst-6, function in a linear signaling pathway and glypican/lon-2 and HS 2-O-sulfotransferase, hst-2, function together in a pathway that is parallel to sdn-1 and hst-6. These results suggest core protein specific HS modifications that are critical for HSN migration. In C. elegans, the core protein specificity of distinct HS modifications may be in part regulated at the level of tissue specific expression of genes encoding for HSPGs and HS modifying enzymes. Genetic analysis reveals that there is a delicate balance of HS modifications and eliminating one HS modifying enzyme in a compromised genetic background leads to significant changes in the overall phenotype. These findings are of importance with the view of HS as a critical regulator of cell signaling in normal development and disease

Movement of the human foot in 100 pain free individuals aged 18–45 : implications for understanding normal foot function

Background: Understanding motion in the normal healthy foot is a prerequisite for understanding the effects of pathology and thereafter setting targets for interventions. Quality foot kinematic data from healthy feet will also assist the development of high quality and research based clinical models of foot biomechanics. To address gaps in the current literature we aimed to describe 3D foot kinematics using a 5 segment foot model in a population of 100 pain free individuals. Methods: Kinematics of the leg, calcaneus, midfoot, medial and lateral forefoot and hallux were measured in 100 self reported healthy and pain free individuals during walking. Descriptive statistics were used to characterise foot movements. Contributions from different foot segments to the total motion in each plane were also derived to explore functional roles of different parts of the foot. Results: Foot segments demonstrated greatest motion in the sagittal plane, but large ranges of movement in all planes. All foot segments demonstrated movement throughout gait, though least motion was observed between the midfoot and calcaneus. There was inconsistent evidence of movement coupling between joints. There were clear differences in motion data compared to foot segment models reported in the literature. Conclusions: The data reveal the foot is a multiarticular structure, movements are complex, show incomplete evidence of coupling, and vary person to person. The data provide a useful reference data set against which future experimental data can be compared and may provide the basis for conceptual models of foot function based on data rather than anecdotal observations

Are language and social communication intact in children with congenital visual impairment at school age?

Background:  Development of children with congenital visual impairment (VI) has been associated with vulnerable socio-communicative outcomes often bearing striking similarities to those of sighted children with autism.1 To date, very little is known about language and social communication in children with VI of normal intelligence. Methods:  We examined the presentation of language and social communication of 15 children with VI and normal-range verbal intelligence, age 6–12 years, using a standardised language assessment and parental reports of everyday social and communicative behaviours. Their profiles were compared to those of typically developing sighted children of similar age and verbal ability. Results:  Compared to their sighted peers, and relative to their own good and potentially superior structural language skills, children with VI showed significantly poorer use of language for social purposes. Pragmatic language weaknesses were a part of a broader socio-communicative profile of difficulties, present in a substantial proportion of these children and consistent with the pattern found in sighted children with autism. Conclusions:  There are ongoing socio-communicative and pragmatic language difficulties in children with congenital VI at school age, despite their good intellectual abilities and advanced linguistic skills. Further research is required to unpack the underlying causes and factors maintaining this vulnerability in such children

Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction

<b>Background</b> The widely used k top scoring pair (k-TSP) algorithm is a simple yet powerful parameter-free classifier. It owes its success in many cancer microarray datasets to an effective feature selection algorithm that is based on relative expression ordering of gene pairs. However, its general robustness does not extend to some difficult datasets, such as those involving cancer outcome prediction, which may be due to the relatively simple voting scheme used by the classifier. We believe that the performance can be enhanced by separating its effective feature selection component and combining it with a powerful classifier such as the support vector machine (SVM). More generally the top scoring pairs generated by the k-TSP ranking algorithm can be used as a dimensionally reduced subspace for other machine learning classifiers.<p></p> <b>Results</b> We developed an approach integrating the k-TSP ranking algorithm (TSP) with other machine learning methods, allowing combination of the computationally efficient, multivariate feature ranking of k-TSP with multivariate classifiers such as SVM. We evaluated this hybrid scheme (k-TSP+SVM) in a range of simulated datasets with known data structures. As compared with other feature selection methods, such as a univariate method similar to Fisher's discriminant criterion (Fisher), or a recursive feature elimination embedded in SVM (RFE), TSP is increasingly more effective than the other two methods as the informative genes become progressively more correlated, which is demonstrated both in terms of the classification performance and the ability to recover true informative genes. We also applied this hybrid scheme to four cancer prognosis datasets, in which k-TSP+SVM outperforms k-TSP classifier in all datasets, and achieves either comparable or superior performance to that using SVM alone. In concurrence with what is observed in simulation, TSP appears to be a better feature selector than Fisher and RFE in some of the cancer datasets.<p></p> <b>Conclusions</b> The k-TSP ranking algorithm can be used as a computationally efficient, multivariate filter method for feature selection in machine learning. SVM in combination with k-TSP ranking algorithm outperforms k-TSP and SVM alone in simulated datasets and in some cancer prognosis datasets. Simulation studies suggest that as a feature selector, it is better tuned to certain data characteristics, i.e. correlations among informative genes, which is potentially interesting as an alternative feature ranking method in pathway analysis

Time separation as a hidden variable to the Copenhagen school of quantum mechanics

The Bohr radius is a space-like separation between the proton and electron in the hydrogen atom. According to the Copenhagen school of quantum mechanics, the proton is sitting in the absolute Lorentz frame. If this hydrogen atom is observed from a different Lorentz frame, there is a time-like separation linearly mixed with the Bohr radius. Indeed, the time-separation is one of the essential variables in high-energy hadronic physics where the hadron is a bound state of the quarks, while thoroughly hidden in the present form of quantum mechanics. It will be concluded that this variable is hidden in Feynman's rest of the universe. It is noted first that Feynman's Lorentz-invariant differential equation for the bound-state quarks has a set of solutions which describe all essential features of hadronic physics. These solutions explicitly depend on the time separation between the quarks. This set also forms the mathematical basis for two-mode squeezed states in quantum optics, where both photons are observable, but one of them can be treated a variable hidden in the rest of the universe. The physics of this two-mode state can then be translated into the time-separation variable in the quark model. As in the case of the un-observed photon, the hidden time-separation variable manifests itself as an increase in entropy and uncertainty.Comment: LaTex 10 pages with 5 figure. Invited paper presented at the Conference on Advances in Quantum Theory (Vaxjo, Sweden, June 2010), to be published in one of the AIP Conference Proceedings serie

Wastewater-based epidemiology in hazard forecasting and early-warning systems for global health risks

With the advent of the SARS-CoV-2 pandemic, Wastewater-Based Epidemiology (WBE) has been applied to track community infection in cities worldwide and has proven succesful as an early warning system for identification of hotspots and changingprevalence of infections (both symptomatic and asymptomatic) at a city or sub-city level. Wastewater is only one of environmental compartments that requires consideration. In this manuscript, we have critically evaluated the knowledge-base and preparedness for building early warning systems in a rapidly urbanising world, with particular attention to Africa, which experiences rapid population growth and urbanisation. We have proposed a Digital Urban Environment Fingerprinting Platform (DUEF) – a new approach in hazard forecasting and early-warning systems for global health risks and an extension to the existing concept of smart cities. The urban environment (especially wastewater) contains a complex mixture of substances including toxic chemicals, infectious biological agents and human excretion products. DUEF assumes that these specific endo- and exogenous residues, anonymously pooled by communities’ wastewater, are indicative of community-wide exposure and the resulting effects. DUEF postulates that the measurement of the substances continuously and anonymously pooled by the receiving environment (sewage, surface water, soils and air), can provide near real-time dynamic information about the quantity and type of physical, biological or chemical stressors to which the surveyed systems are exposed, and can create a risk profile on the potential effects of these exposures. Successful development and utilisation of a DUEF globally requires a tiered approach including: Stage I: network building, capacity building, stakeholder engagement as well as a conceptual model, followed by Stage II: DUEF development, Stage III: implementation, and Stage IV: management and utilization. We have identified four key pillars required for the establishment of a DUEF framework: (1) Environmental fingerprints, (2) Socioeconomic fingerprints, (3) Statistics and modelling and (4) Information systems. This manuscript critically evaluates the current knowledge base within each pillar and provides recommendations for further developments with an aim of laying grounds for successful development of global DUEF platforms

Oldest pathology in a tetrapod bone illuminates the origin of terrestrial vertebrates

The origin of terrestrial tetrapods was a key event in vertebrate evolution, yet how and when it occurred remains obscure, due to scarce fossil evidence. Here, we show that the study of palaeopathologies, such as broken and healed bones, can help elucidate poorly understood behavioural transitions such as this. Using high-resolution finite element analysis, we demonstrate that the oldest known broken tetrapod bone, a radius of the primitive stem tetrapod Ossinodus pueri from the mid-Viséan (333 million years ago) of Australia, fractured under a high-force, impact-type loading scenario. The nature of the fracture suggests that it most plausibly occurred during a fall on land. Augmenting this are new osteological observations, including a preferred directionality to the trabecular architecture of cancellous bone. Together, these results suggest that Ossinodus, one of the first large (>2m length) tetrapods, spent a significant proportion of its life on land. Our findings have important implications for understanding the temporal, biogeographical and physiological contexts under which terrestriality in vertebrates evolved. They push the date for the origin of terrestrial tetrapods further back into the Carboniferous by at least two million years. Moreover, they raise the possibility that terrestriality in vertebrates first evolved in large tetrapods in Gondwana rather than in small European forms, warranting a re-evaluation of this important evolutionary event

Functional assessment of coronary artery flow using adenosine stress dual-energy CT: a preliminary study

We attempted to assess coronary artery flow using adenosine-stress and dual-energy mode with dual-source CT (DE-CT). Data of 18 patients with suspected coronary arteries disease who had undergone cardiac DE-CT were retrospectively analyzed. The patients were divided into two groups: 10 patients who performed adenosine stress CT, and 8 patients who performed rest CT as controls. We reconstructed an iodine map and composite images at 120 kV (120 kV images) using raw data with scan parameters of 100 and 140 kV. We measured mean attenuation in the coronary artery proximal to the distal portion on both the iodine map and 120 kV images. Coronary enhancement ratio (CER) was calculated by dividing mean attenuation in the coronary artery by attenuation in the aortic root, and was used as an estimate of coronary enhancement. Coronary stenosis was identified as a reduction in diameter of >50% on CT angiogram, and myocardial ischemia was diagnosed by adenosine-stress myocardial perfusion scintigraphy. The iodine map showed that CER was significantly lower for ischemic territories (0.76 ± 0.06) or stenosed coronary arteries (0.77 ± 0.06) than for non-ischemic territories (0.95 ± 0.21, P = 0.02) or non-stenosed coronary arteries (1.07 ± 0.33, P < 0.001). The 120 kV images showed no difference in CER between these two groups. Use of CER on the iodine map separated ischemic territories from non-ischemic territories with a sensitivity of 86% and a specificity of 75%. Our quantification is the first non-invasive analytical technique for assessment of coronary artery flow using cardiac CT. CER on the iodine map is a candidate method for demonstration of alteration in coronary artery flow under adenosine stress, which is related to the physiological significance of coronary artery disease

Outcomes of allogeneic stem cell transplantation among patients with acute myeloid leukemia presenting active disease: Experience of a single European Comprehensive Cancer Center

Introduction: Allogeneic hematopoietic stem cell transplantation (ASCT) represents a potentially curative approach for patients with relapsed or refractory acute myeloid leukemia (AML). We report the outcome of relapsed/refractory AML patients treated with ASCT.Method: A retrospective cohort from 1994 to 2013 that included 61 patients with diagnosis of relapsed/refractory AML. Outcomes of interest were transplant-related mortality (TRM), incidence of acute and chronic graft-versus-host disease (GVHD), relapse incidence, progression-free survival (PFS) and overall survival (OS). Statistical significance was set at p<0.05.Results: The median age was 61 years (range 1 to 65). The cumulative incidence of 90 days, 1 year, and 3 years TRM were 60%, 26.7%, and 13.3%, respectively (p< 0.001). The incidence of relapse was 21.7% at 1 year, 13% at 3 years, and 8.7% at 5 years. Median OS was estimated to be 8 months (95CI 3.266-12.734) and median PFS, 3 months (95CI 1.835-4.165).Conclusion: In our cohort, TRM in first years after ASCT remains considerable, but ASCT in this setting seems to be a good choice for AML patients with active disease. However, novel approaches are needed to reduce TRM and relapse in this set of patients