A search for polycyclic aromatic hydrocarbons over the Martian South Polar Residual Cap

We present our research on compositional mapping of the Martian South Polar Residual Cap (SPRC), especially the detection of organic signatures within the dust content of the ice, based on hyperspectral data analysis. The SPRC is the main region of interest for this investigation, because of the unique CO 2 ice sublimation features that cover the surface. These flat floored, circular depressions are highly dynamic, and we infer frequently expose dust particle s previously trapped within the ice during the wintertime. Here we identify suitable regions for potential dust exposure on the SPRC, and utilise data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) on board NASA's Mars Reconnaissance Orbiter (MRO) satellite to examine infrared spectra of dark regions assumed to be composed mainly of dust particles to establish their mineral composition, to eliminate the effects of ices on sub-pixel dusty features, and to look for signatures indicative of Polycyclic Aromatic Hydrocarbons (PAHs). Spectral mapping has identified compositional differences between depression rims and the majority of the SPRC and CRISM spectra have been corrected to minimise the influence of CO 2 ice. Whilst no conclusive evidence for PAHs has been found within the detectability limits of the CRISM instrument, depression rims are shown to have higher water content than regions of featureless ice, and there are possible indications of magnesium carbonate within the dark, dusty regions

The Detectability Limit of Organic Molecules Within Mars South Polar Laboratory Analogs

A series of laboratory experiments was carried out in order to generate a diagnostic spectrum for Polycyclic Aromatic Hydrocarbons (PAHs) of astrobiological interest in the context of the Martian South Polar Residual Cap (SPRC), to establish PAH spectral features more easily detectable in CO2 ice (mixed with small amounts of H2O ice) than the previously reported absorption feature at 3.29 µm in order to constrain their detectability limit. There is currently no existing literature on PAH detection within SPRC features, making this work novel and impactful given the recent discovery of a possible subglacial lake beneath the Martian South Pole. Although they have been detected in Martian meteorites, PAHs have not been detected yet on Mars, possibly due to the deleterious effects of ultraviolet radiation on the surface of the planet. SPRC features may provide protection to fragile molecules, and this work seeks to provide laboratory data to improve interpretation of orbital remote sensing spectroscopic imaging data. We also ascertain the effect of CO2 ice sublimation on organic spectra, as well as provide PAH reference spectra in mixtures relevant to Mars. A detectability limit of ∼0.04% has been recorded for observing PAHs in CO2 ice using laboratory instrument parameters emulating those of the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM), with new spectral slope features revealed between 0.7 and 1.1 µm, and absorption features at 1.14 and, most sensitively, at 1.685 µm. Mars regolith analogue mixed with a concentration of 1.5% PAHs resulted in no discernible organic spectral features. These detectability limits measured in the laboratory are discussed and extrapolated to the effective conditions on the Mars South Polar Cap in terms of dust and water ice abundance and CO2 ice grain size for both the main perennial cap and the H2O ice-dust sublimation lag deposit

Applications of interpretability in deep learning models for ophthalmology

PURPOSE OF REVIEW: In this article, we introduce the concept of model interpretability, review its applications in deep learning models for clinical ophthalmology, and discuss its role in the integration of artificial intelligence in healthcare. RECENT FINDINGS: The advent of deep learning in medicine has introduced models with remarkable accuracy. However, the inherent complexity of these models undermines its users' ability to understand, debug and ultimately trust them in clinical practice. Novel methods are being increasingly explored to improve models' 'interpretability' and draw clearer associations between their outputs and features in the input dataset. In the field of ophthalmology, interpretability methods have enabled users to make informed adjustments, identify clinically relevant imaging patterns, and predict outcomes in deep learning models. SUMMARY: Interpretability methods support the transparency necessary to implement, operate and modify complex deep learning models. These benefits are becoming increasingly demonstrated in models for clinical ophthalmology. As quality standards for deep learning models used in healthcare continue to evolve, interpretability methods may prove influential in their path to regulatory approval and acceptance in clinical practice

Results of consecutive training procedures in pediatric cardiac surgery

This report from a single institution describes the results of consecutive pediatric heart operations done by trainees under the supervision of a senior surgeon. The 3.1% mortality seen in 1067 index operations is comparable across procedures and risk bands to risk-stratified results reported by the Society of Thoracic Surgeons. With appropriate mentorship, surgeons-in-training are able to achieve good results as first operators

Evaluation of demand in a rural English hospital emergency department

The purpose of this article is to analyse the patient demand placed on a rural district general hospital (DGH) emergency department within the context of the Purpose, Process, People (PPP) framework used in the private sector. This analysis was undertaken to inform wider evaluation of the implementation of the enterprise culture—the NHS policy to adopt private sector best practice to produce resource use, quality and efficiency improvements. The article concludes with a view that the PPP framework provides methods of calculating the level of discharge necessary to meet the four-hour wait target. Data describing the characteristics and patterns of attending patients can be used to develop an emergency department’s processes and people to achieve its time-based target

Supersymmetric geometries of IIA supergravity I

IIA supergravity backgrounds preserving one supersymmetry locally admit four types of Killing spinors distinguished by the orbits of $Spin(9,1)$ on the space of spinors. We solve the Killing spinor equations of IIA supergravity with and without cosmological constant for Killing spinors representing two of these orbits, with isotropy groups $Spin(7)$ and $Spin(7)\ltimes\mathbb{R}^8$. In both cases, we identify the geometry of spacetime and express the fluxes in terms of the geometry. We find that the geometric constraints of backgrounds with a $Spin(7)\ltimes\mathbb{R}^8$ invariant Killing spinor are identical to those found for heterotic backgrounds preserving one supersymmetry.Comment: 21 page

Exome sequencing followed by large-scale genotyping suggests a limited role for moderately rare risk factors of strong effect in schizophrenia.

Schizophrenia is a severe psychiatric disorder with strong heritability and marked heterogeneity in symptoms, course, and treatment response. There is strong interest in identifying genetic risk factors that can help to elucidate the pathophysiology and that might result in the development of improved treatments. Linkage and genome-wide association studies (GWASs) suggest that the genetic basis of schizophrenia is heterogeneous. However, it remains unclear whether the underlying genetic variants are mostly moderately rare and can be identified by the genotyping of variants observed in sequenced cases in large follow-up cohorts or whether they will typically be much rarer and therefore more effectively identified by gene-based methods that seek to combine candidate variants. Here, we consider 166 persons who have schizophrenia or schizoaffective disorder and who have had either their genomes or their exomes sequenced to high coverage. From these data, we selected 5,155 variants that were further evaluated in an independent cohort of 2,617 cases and 1,800 controls. No single variant showed a study-wide significant association in the initial or follow-up cohorts. However, we identified a number of case-specific variants, some of which might be real risk factors for schizophrenia, and these can be readily interrogated in other data sets. Our results indicate that schizophrenia risk is unlikely to be predominantly influenced by variants just outside the range detectable by GWASs. Rather, multiple rarer genetic variants must contribute substantially to the predisposition to schizophrenia, suggesting that both very large sample sizes and gene-based association tests will be required for securely identifying genetic risk factors. © 2012 The American Society of Human Genetics

Can exercise affect immune function to increase susceptibility to infection?

Multiple studies in humans and animals have demonstrated the profound impact that exercise can have on the immune system. There is a general consensus that regular bouts of short-lasting (i.e. up to 45 minutes) moderate intensity exercise is beneficial for host immune defense, particularly in older adults and people with chronic diseases. In contrast, infection burden is reported to be high among high performance athletes and second only to injury for the number of training days lost during preparation for major sporting events. This has shaped the common view that arduous exercise (i.e. those activities practiced by high performance athletes/ military personnel that greatly exceed recommended physical activity guidelines) can suppress immunity and increase infection risk. However, the idea that exercise per se can suppress immunity and increase infection risk independently of the many other factors (e.g. anxiety, sleep disruption, travel, exposure, nutritional deficits, environmental extremes, etc.) experienced by these populations has recently been challenged. The purpose of this debate article was to solicit opposing arguments centered around this fundamental question in the exercise immunology field: can exercise affect immune function to increase susceptibility to infection. Issues that were contested between the debating groups include: (i) whether or not athletes are more susceptible to infection (mainly of the upper respiratory tract) than the general population; (ii) whether exercise per se is capable of altering immunity to increase infection risk independently of the multiple factors that activate shared immune pathways and are unique to the study populations involved; (iii) the usefulness of certain biomarkers and the interpretation of in vitro and in vivo data to monitor immune health in those who perform arduous exercise; and (iv) the quality of scientific evidence that has been used to substantiate claims for and against the potential negative effects of arduous exercise on immunity and infection risk. A key point of agreement between the groups is that infection susceptibility has a multifactorial underpinning. An issue that remains to be resolved is whether exercise per se is a causative factor of increased infection risk in athletes. This article should provide impetus for more empirical research to unravel the complex questions that surround this contentious issue in the field of exercise immunology