Exploiting Anopheles responses to thermal, odour and visual stimuli to improve surveillance and control of malaria

Mosquito surveillance and control are at the heart of efforts to eliminate malaria, however, there remain significant gaps in our understanding of mosquito behaviour that impede innovation. We hypothesised that a combination of human-associated stimuli could be used to attract and kill malaria vectors more successfully than individual stimuli, and at least as well as a real human. To test this in the field, we quantified Anopheles responses to olfactory, visual and thermal stimuli in Burkina Faso using a simple adhesive trap. Traps baited with human odour plus high contrast visual stimuli caught more Anopheles than traps with odour alone, showing that despite their nocturnal habit, malaria vectors make use of visual cues in host-seeking. The best performing traps, however, combined odour and visual stimuli with a thermal signature in the range equivalent to human body temperature. When tested against a human landing catch during peak mosquito abundance, this “host decoy” trap caught nearly ten times the number of Anopheles mosquitoes caught by a human collector. Exploiting the behavioural responses of mosquitoes to the entire suite of host stimuli promises to revolutionise vector surveillance and provide new paradigms in disease control

Experiences and insights from the collection of a novel multimedia EEG dataset

There is a growing interest in utilising novel signal sources such as EEG (Electroencephalography) in multimedia research. When using such signals, subtle limitations are often not readily apparent without significant domain expertise. Multimedia research outputs incorporating EEG signals can fail to be replicated when only minor modifications have been made to an experiment or seemingly unimportant (or unstated) details are changed. This can lead to overoptimistic or overpessimistic viewpoints on the potential real-world utility of these signals in multimedia research activities. This paper describes an EEG/MM dataset and presents a summary of distilled experiences and knowledge gained during the preparation (and utilisiation) of the dataset that supported a collaborative neural-image labelling benchmarking task. The goal of this task was to collaboratively identify machine learning approaches that would support the use of EEG signals in areas such as image labelling and multimedia modeling or retrieval. The contributions of this paper can be listed thus; a template experimental paradigm is proposed (along with datasets and a baseline system) upon which researchers can explore multimedia image labelling using a brain-computer interface, learnings regarding commonly encountered issues (and useful signals) when conducting research that utilises EEG in multimedia contexts are provided, and finally insights are shared on how an EEG dataset was used to support a collaborative neural-image labelling benchmarking task and the valuable experiences gained

Nonmotor Symptoms in LRRK2 G2019S Associated Parkinson's Disease

BACKGROUND: Idiopathic Parkinson's disease (IPD) and LRRK2-associated PD (LRRK2-PD) might be expected to differ clinically since the neuropathological substrate of LRRK2-PD is heterogeneous. The range and severity of extra-nigral nonmotor features associated with LRRK2 mutations is also not well-defined. OBJECTIVE: To evaluate the prevalence and time of onset of nonmotor symptoms (NMS) in LRRK2-PD patients. METHODS: The presence of hyposmia and of neuropsychiatric, dysautonomic and sleep disturbances was assessed in 33 LRRK2-G2019S-PD patients by standardized questionnaires and validated scales. Thirty-three IPD patients, matched for age, gender, duration of parkinsonism and disease severity and 33 healthy subjects were also evaluated. RESULTS: University of Pennsylvania Smell Identification Test (UPSIT) scores in LRRK2-G2019S-PD were higher than those in IPD (23.5±6.8 vs 18.4±6.0; p = 0.002), and hyposmia was less frequent in G2019S carriers than in IPD (39.4% vs 75.8%; p = 0.01). UPSIT scores were significantly higher in females than in males in LRRK2-PD patients (26.9±4.7 vs 19.4±6.8; p<0.01). The frequency of sleep and neuropsychiatric disturbances and of dysautonomic symptoms in LRRK2-G2019S-PD was not significantly different from that in IPD. Hyposmia, depression, constipation and excessive daytime sleepiness, were reported to occur before the onset of classical motor symptoms in more than 40% of LRRK2-PD patients in whom these symptoms were present at the time of examination. CONCLUSION: Neuropsychiatric, dysautonomic and sleep disturbances occur as frequently in patients with LRRK2-G2019S-PD as in IPD but smell loss was less frequent in LRRK2-PD. Like in IPD, disturbances such as hyposmia, depression, constipation and excessive daytime sleepiness may antedate the onset of classical motor symptoms in LRRK2-G2019S-PD

Candidate gene association study in pediatric acute lymphoblastic leukemia evaluated by Bayesian network based Bayesian multilevel analysis of relevance

Background: We carried out a candidate gene association study in pediatric acute lymphoblastic leukemia (ALL) to identify possible genetic risk factors in a Hungarian population. Methods: The results were evaluated with traditional statistical methods and with our newly developed Bayesian network based Bayesian multilevel analysis of relevance (BN-BMLA) method. We collected genomic DNA and clinical data from 543 children, who underwent chemotherapy due to ALL, and 529 healthy controls. Altogether 66 single nucleotide polymorphisms (SNPs) in 19 candidate genes were genotyped. Results: With logistic regression, we identified 6 SNPs in the ARID5B and IKZF1 genes associated with increased risk to B-cell ALL, and two SNPs in the STAT3 gene, which decreased the risk to hyperdiploid ALL. Because the associated SNPs were in linkage in each gene, these associations corresponded to one signal per gene. The odds ratio (OR) associated with the tag SNPs were: OR = 1.69, P = 2.22x10-7 for rs4132601 (IKZF1), OR = 1.53, P = 1.95x10-5 for rs10821936 (ARID5B) and OR = 0.64, P = 2.32x10-4 for rs12949918 (STAT3). With the BN-BMLA we confirmed the findings of the frequentist-based method and received additional information about the nature of the relations between the SNPs and the disease. E.g. the rs10821936 in ARID5B and rs17405722 in STAT3 showed a weak interaction, and in case of T-cell lineage sample group, the gender showed a weak interaction with three SNPs in three genes. In the hyperdiploid patient group the BN-BMLA detected a strong interaction among SNPs in the NOTCH1, STAT1, STAT3 and BCL2 genes. Evaluating the survival rate of the patients with ALL, the BN-BMLA showed that besides risk groups and subtypes, genetic variations in the BAX and CEBPA genes might also influence the probability of survival of the patients. Conclusions: In the present study we confirmed the roles of genetic variations in ARID5B and IKZF1 in the susceptibility to B-cell ALL. With the newly developed BN-BMLA method several gene-gene, gene-phenotype and phenotype-phenotype connections were revealed. We showed several advantageous features of the new method, and suggested that in gene association studies the BN-BMLA might be a useful supplementary to the traditional frequentist-based statistical method

Sex, Ecology and the Brain: Evolutionary Correlates of Brain Structure Volumes in Tanganyikan Cichlids

Analyses of the macroevolutionary correlates of brain structure volumes allow pinpointing of selective pressures influencing specific structures. Here we use a multiple regression framework, including phylogenetic information, to analyze brain structure evolution in 43 Tanganyikan cichlid species. We analyzed the effect of ecological and sexually selected traits for species averages, the effect of ecological traits for each sex separately and the influence of sexual selection on structure dimorphism. Our results indicate that both ecological and sexually selected traits have influenced brain structure evolution. The patterns observed in males and females generally followed those observed at the species level. Interestingly, our results suggest that strong sexual selection is associated with reduced structure volumes, since all correlations between sexually selected traits and structure volumes were negative and the only statistically significant association between sexual selection and structure dimorphism was also negative. Finally, we previously found that monoparental female care was associated with increased brain size. However, here cerebellum and hypothalamus volumes, after controlling for brain size, associated negatively with female-only care. Thus, in accord with the mosaic model of brain evolution, brain structure volumes may not respond proportionately to changes in brain size. Indeed selection favoring larger brains can simultaneously lead to a reduction in relative structure volumes

Getting a Head Start: Diet, Sub-Adult Growth, and Associative Learning in a Seed-Eating Passerine

Developmental stress, and individual variation in response to it, can have important fitness consequences. Here we investigated the consequences of variable dietary protein on the duration of growth and associative learning abilities of zebra finches, Taeniopygia guttata, which are obligate graminivores. The high-protein conditions that zebra finches would experience in nature when half-ripe seed is available were mimicked by the use of egg protein to supplement mature seed, which is low in protein content. Growth rates and relative body proportions of males reared either on a low-protein diet (mature seed only) or a high-protein diet (seed plus egg) were determined from body size traits (mass, head width, and tarsus) measured at three developmental stages. Birds reared on the high-protein diet were larger in all size traits at all ages, but growth rates of size traits showed no treatment effects. Relative head size of birds reared on the two diets differed from age day 95 onward, with high-diet birds having larger heads in proportion to both tarsus length and body mass. High-diet birds mastered an associative learning task in fewer bouts than those reared on the low-protein diet. In both diet treatments, amount of sub-adult head growth varied directly, and sub-adult mass change varied inversely, with performance on the learning task. Results indicate that small differences in head growth during the sub-adult period can be associated with substantial differences in adult cognitive performance. Contrary to a previous report, we found no evidence for growth compensation among birds on the low-protein diet. These results have implications for the study of vertebrate cognition, developmental stress, and growth compensation

Multiple Determinants of Whole and Regional Brain Volume among Terrestrial Carnivorans

Mammalian brain volumes vary considerably, even after controlling for body size. Although several hypotheses have been proposed to explain this variation, most research in mammals on the evolution of encephalization has focused on primates, leaving the generality of these explanations uncertain. Furthermore, much research still addresses only one hypothesis at a time, despite the demonstrated importance of considering multiple factors simultaneously. We used phylogenetic comparative methods to investigate simultaneously the importance of several factors previously hypothesized to be important in neural evolution among mammalian carnivores, including social complexity, forelimb use, home range size, diet, life history, phylogeny, and recent evolutionary changes in body size. We also tested hypotheses suggesting roles for these variables in determining the relative volume of four brain regions measured using computed tomography. Our data suggest that, in contrast to brain size in primates, carnivoran brain size may lag behind body size over evolutionary time. Moreover, carnivore species that primarily consume vertebrates have the largest brains. Although we found no support for a role of social complexity in overall encephalization, relative cerebrum volume correlated positively with sociality. Finally, our results support negative relationships among different brain regions after accounting for overall endocranial volume, suggesting that increased size of one brain regions is often accompanied by reduced size in other regions rather than overall brain expansion

Quality of life data as prognostic indicators of survival in cancer patients: an overview of the literature from 1982 to 2008

<p>Abstract</p> <p>Background</p> <p>Health-related quality of life and survival are two important outcome measures in cancer research and practice. The aim of this paper is to examine the relationship between quality of life data and survival time in cancer patients.</p> <p>Methods</p> <p>A review was undertaken of all the full publications in the English language biomedical journals between 1982 and 2008. The search was limited to cancer, and included the combination of keywords 'quality of life', 'patient reported-outcomes' 'prognostic', 'predictor', 'predictive' and 'survival' that appeared in the titles of the publications. In addition, each study was examined to ensure that it used multivariate analysis. Purely psychological studies were excluded. A manual search was also performed to include additional papers of potential interest.</p> <p>Results</p> <p>A total of 451 citations were identified in this rapid and systematic review of the literature. Of these, 104 citations on the relationship between quality of life and survival were found to be relevant and were further examined. The findings are summarized under different headings: heterogeneous samples of cancer patients, lung cancer, breast cancer, gastro-oesophageal cancers, colorectal cancer, head and neck cancer, melanoma and other cancers. With few exceptions, the findings showed that quality of life data or some aspects of quality of life measures were significant independent predictors of survival duration. Global quality of life, functioning domains and symptom scores - such as appetite loss, fatigue and pain - were the most important indicators, individually or in combination, for predicting survival times in cancer patients after adjusting for one or more demographic and known clinical prognostic factors.</p> <p>Conclusion</p> <p>This review provides evidence for a positive relationship between quality of life data or some quality of life measures and the survival duration of cancer patients. Pre-treatment (baseline) quality of life data appeared to provide the most reliable information for helping clinicians to establish prognostic criteria for treating their cancer patients. It is recommended that future studies should use valid instruments, apply sound methodological approaches and adequate multivariate statistical analyses adjusted for socio-demographic characteristics and known clinical prognostic factors with a satisfactory validation strategy. This strategy is likely to yield more accurate and specific quality of life-related prognostic variables for specific cancers.</p

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta