Atypical presentation of an oesophageal carcinoma with metastases to the left buttock: a case report

© 2009 Smyth et al; licensee Cases Network Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Machine learning reveals singing rhythms of male Pacific field crickets are clock controlled

Circadian rhythms are ubiquitous in nature and endogenous circadian clocks drive the daily expression of many fitness-related behaviors. However, little is known about whether such traits are targets of selection imposed by natural enemies. In Hawaiian populations of the nocturnally active Pacific field cricket (Teleogryllus oceanicus), males sing to attract mates, yet sexually selected singing rhythms are also subject to natural selection from the acoustically orienting and deadly parasitoid fly, Ormia ochracea. Here, we use T. oceanicus to test whether singing rhythms are endogenous and scheduled by circadian clocks, making them possible targets of se lection imposed by flies. We also develop a novel audio-to-circadian analysis pipeline, capable of extracting useful parameters from which to train machine learning algorithms and process large quantities of audio data. Singing rhythms fulfilled all criteria for endogenous circadian clock control, including being driven by photoschedule, self-sustained periodicity of approximately 24 h, and being robust to variation in temperature. Furthermore, singing rhythms varied across individuals, which might suggest genetic variation on which natural and sexual selection pressures can act. Sexual signals and ornaments are well-known targets of selection by natural enemies, but our findings indicate that the circadian timing of those traits’ expression may also determine fitnes

Adaptive periodicity in the infectivity of malaria gametocytes to mosquitoes

Daily rhythms in behaviour, physiology, and molecular processes are expected to enable organisms to appropriately schedule activities according to consequences of the daily rotation of the Earth. For parasites, this includes capitalizing on periodicity in transmission opportunities and for hosts/vectors, this may select for rhythms in immune defence. We examine rhythms in the density and infectivity of transmission forms (gametocytes) of rodent malaria parasites in the host’s blood, parasite development inside mosquito vectors, and potential for onwards transmission. Furthermore, we simultaneously test whether mosquitoes exhibit rhythms in susceptibility. We reveal that at night, gametocytes are twice as infective, despite being less numerous in the blood. Enhanced infectiousness at night interacts with mosquito rhythms to increase sporozoite burdens four-fold when mosquitoes feed during their rest phase. Thus, changes in mosquito biting time (due to bed nets) may render gametocytes less infective, but this is compensated for by the greater mosquito susceptibility

Finding the principles of the commons: a report of the Force11 Scholarly Communications Working Group

Open access[No abstract available]Ye

Detection of anti-correlation of hot and cold baryons in galaxy clusters

The largest clusters of galaxies in the Universe contain vast amounts of dark matter, plus baryonic matter in two principal phases, a majority hot gas component and a minority cold stellar phase comprising stars, compact objects, and low-temperature gas. Hydrodynamic simulations indicate that the highest-mass systems retain the cosmic fraction of baryons, a natural consequence of which is anti-correlation between the masses of hot gas and stars within dark matter halos of fixed total mass. We report observational detection of this anti-correlation based on 4 elements of a 9 x 9-element covariance matrix for nine cluster properties, measured from multi-wavelength observations of 41 clusters from the Local Cluster Substructure Survey. These clusters were selected using explicit and quantitative selection rules that were then encoded in our hierarchical Bayesian model. Our detection of anti-correlation is consistent with predictions from contemporary hydrodynamic cosmological simulations that were not tuned to reproduce this signal.Peer reviewe

Effect of oxygen on the expression of renin-angiotensin system components in a human trophoblast cell line

During the first trimester, normal placental development occurs in a low oxygen environment that is known to stimulate angiogenesis via upregulation of vascular endothelial growth factor (VEGF). Expression of the placental renin-angiotensin system (RAS) is highest in early pregnancy. While the RAS and oxygen both stimulate angiogenesis, how they interact within the placenta is unknown. We postulated that low oxygen increases expression of the proangiogenic RAS pathway and that this is associated with increased VEGF in a first trimester human trophoblast cell line (HTR-8/SVneo). HTR-8/SVneo cells were cultured in one of three oxygen tensions (1%, 5% and 20%). RAS and VEGF mRNA expression were determined by qPCR. Prorenin, angiotensin converting enzyme (ACE) and VEGF protein levels in the supernatant, as well as prorenin and ACE in cell lysates, were measured using ELISAs. Low oxygen significantly increased the expression of both angiotensin II type 1 receptor (AGTR1) and VEGF (both P < 0.05). There was a positive correlation between AGTR1 and VEGF expression at low oxygen (r = 0.64, P < 0.005). Corresponding increases in VEGF protein were observed with low oxygen (P < 0.05). Despite no change in ACE1 mRNA expression, ACE levels in the supernatant increased with low oxygen (1% and 5%, P < 0.05). Expression of other RAS components did not change. Low oxygen increased AGTR1 and VEGF expression, as well as ACE and VEGF protein levels, suggesting that the proangiogenic RAS pathway is activated. This highlights a potential role for the placental RAS in mediating the proangiogenic effects of low oxygen in placental development

Conventional and unconventional T cell responses contribute to the prediction of clinical outcome and causative bacterial pathogen in sepsis patients

Sepsis is characterised by a dysfunctional host response to infection culminating in life-threatening organ failure that requires complex patient management and rapid intervention. Timely diagnosis of the underlying cause of sepsis is crucial, and identifying those at risk of complications and death is imperative for triaging treatment and resource allocation. Here, we explored the potential of explainable machine learning models to predict mortality and causative pathogen in sepsis patients. By using a modelling pipeline employing multiple feature selection algorithms, we demonstrate the feasibility to identify integrative patterns from clinical parameters, plasma biomarkers and extensive phenotyping of blood immune cells. Whilst no single variable had sufficient predictive power, models that combined five and more features showed a macro area under the curve (AUC) of 0.85 to predict 90 day mortality after sepsis diagnosis, and a macro AUC of 0.86 to discriminate between Gram-positive and Gram-negative bacterial infections. Parameters associated with the cellular immune response contributed the most to models predictive of 90 day mortality, most notably, the proportion of T cells among PBMCs, together with expression of CXCR3 by CD4+ T cells and CD25 by mucosal-associated invariant T (MAIT) cells. Frequencies of Vδ2+ γδ T cells had the most profound impact on the prediction of Gram-negative infections, alongside other T cell-related variables and total neutrophil count. Overall, our findings highlight the added value of measuring the proportion and activation patterns of conventional and unconventional T cells in the blood of sepsis patients in combination with other immunological, biochemical and clinical parameters

LoCuSS : scaling relations between galaxy cluster mass, gas, and stellar content

We present a simultaneous analysis of galaxy cluster scaling relations between weak-lensing mass and multiple cluster observables, across a wide range of wavelengths, that probe both gas and stellar content. Our new hierarchical Bayesian model simultaneously considers the selection variable alongside all other observables in order to explicitly model intrinsic property covariance and account for selection effects. We apply this method to a sample of 41 clusters at 0.15 <z <0.30, with a well-defined selection criteria based on RASS X-ray luminosity, and observations from Chandra/XMM, SZA, Planck, UKIRT, SUSS, and Subaru. These clusters have well-constrained weak-lensing mass measurements based on Subaru/SuprimeCam observations, which serve as the reference masses in our model. We present 30 scaling relation parameters for 10 properties. All relations probing the intracluster gas are slightly shallower than self-similar predictions, in moderate tension with prior measurements, and the stellar fraction decreases with mass. K-band luminosity has the lowest intrinsic scatter with a 95th percentile of 0.16, while the lowest scatter gas probe is gas mass with a fractional intrinsic scatter of 0.16 +/- 0.03. We find no distinction between the core-excised X-ray or high-resolution Sunyaev-Zel'dovich relations of clusters of different central entropy, but find with modest significance that higher entropy clusters have higher stellar fractions than their lower entropy counterparts. We also report posterior mass estimates from our likelihood model.Peer reviewe

Short-term stability in refractive status despite large fluctuations in glucose levels in diabetes mellitus type 1 and 2

Purpose: This work investigates how short-term changes in blood glucose concentration affect the refractive components of the diabetic eye in patients with long-term Type 1 and Type 2 diabetes. Methods: Blood glucose concentration, refractive error components (mean spherical equivalent MSE, J0, J45), central corneal thickness (CCT), anterior chamber depth (ACD), crystalline lens thickness (LT), axial length (AL) and ocular aberrations were monitored at two-hourly intervals over a 12-hour period in: 20 T1DM patients (mean age ± SD) 38±14 years, baseline HbA1c 8.6±1.9%; 21 T2DM patients (mean age ± SD) 56±11 years, HbA1c 7.5±1.8%; and in 20 control subjects (mean age ± SD) 49±23 years, HbA1c 5.5±0.5%. The refractive and biometric results were compared with the corresponding changes in blood glucose concentration. Results: Blood glucose concentration at different times was found to vary significantly within (p0.05). Minor changes of marginal statistical or optical significance were observed in some biometric parameters. Similarly there were some marginally significant differences between the baseline biometric parameters of well-controlled and poorly-controlled diabetic subjects. Conclusion: This work suggests that normal, short-term fluctuations (of up to about 6 mM/l on a timescale of a few hours) in the blood glucose levels of diabetics are not usually associated with acute changes in refractive error or ocular wavefront aberrations. It is therefore possible that factors other than refractive error fluctuations are sometimes responsible for the transient visual problems often reported by diabetic patients