Social disorganization and history of child sexual abuse against girls in sub-Saharan Africa : a multilevel analysis

Background: Child sexual abuse (CSA) is a considerable public health problem. Less focus has been paid to the role of community level factors associated with CSA. The aim of this study was to examine the association between neighbourhood-level measures of social disorganization and CSA. Methods: We applied multiple multilevel logistic regression analysis on Demographic and Health Survey data for 6,351 adolescents from six countries in sub-Saharan Africa between 2006 and 2008. Results: The percentage of adolescents that had experienced CSA ranged from 1.04% to 5.84%. There was a significant variation in the odds of reporting CSA across the communities, suggesting 18% of the variation in CSA could be attributed to community level factors. Respondents currently employed were more likely to have reported CSA than those who were unemployed (odds ratio [OR] = 2.05, 95% confidence interval [CI] 1.48 to 2.83). Respondents from communities with a high family disruption rate were 57% more likely to have reported CSA (OR=1.57, 95% CI 1.14 to 2.16). Conclusion: We found that exposure to CSA was associated with high community level of family disruption, thus suggesting that neighbourhoods may indeed have significant important effects on exposure to CSA. Further studies are needed to explore pathways that connect the individual and neighbourhood levels, that is, means through which deleterious neighbourhood effects are transmitted to individuals

From Demonstrations to Task-Space Specifications:Using Causal Analysis to Extract Rule Parameterization from Demonstrations

Learning models of user behaviour is an important problem that is broadly applicable across many application domains requiring human-robot interaction. In this work, we show that it is possible to learn generative models for distinct user behavioural types, extracted from human demonstrations, by enforcing clustering of preferred task solutions within the latent space. We use these models to differentiate between user types and to find cases with overlapping solutions. Moreover, we can alter an initially guessed solution to satisfy the preferences that constitute a particular user type by backpropagating through the learned differentiable models. An advantage of structuring generative models in this way is that we can extract causal relationships between symbols that might form part of the user's specification of the task, as manifested in the demonstrations. We further parameterize these specifications through constraint optimization in order to find a safety envelope under which motion planning can be performed. We show that the proposed method is capable of correctly distinguishing between three user types, who differ in degrees of cautiousness in their motion, while performing the task of moving objects with a kinesthetically driven robot in a tabletop environment. Our method successfully identifies the correct type, within the specified time, in 99% [97.8 - 99.8] of the cases, which outperforms an IRL baseline. We also show that our proposed method correctly changes a default trajectory to one satisfying a particular user specification even with unseen objects. The resulting trajectory is shown to be directly implementable on a PR2 humanoid robot completing the same task.Comment: arXiv admin note: substantial text overlap with arXiv:1903.0126

Bayesian paternity analysis and mating patterns in a parasitic nematode, Trichostrongylus tenuis

Mating behaviour is a fundamental aspect of the evolutionary ecology of sexually reproducing species, but one that has been under-researched in parasitic nematodes. We analysed mating behaviour in the parasitic nematode Trichostrongylus tenuis by performing a paternity analysis in a population from a single red grouse host. Paternity of the 150 larval offspring of 25 mothers (sampled from one of the two host caeca) was assigned among 294 candidate fathers (sampled from both caeca). Each candidate father's probability of paternity of each offspring was estimated from 10-locus microsatellite genotypes. Seventy-six (51%) offspring were assigned a father with a probability of >0.8, and the estimated number of unsampled males was 136 (95% credible interval (CI) 77-219). The probability of a male from one caecum fathering an offspring in the other caecum was estimated as 0.024 (95% CI 0.003-0.077), indicating that the junction of the caeca is a strong barrier to dispersal. Levels of promiscuity (defined as the probability of two of an adult's offspring sharing only one parent) were high for both sexes. Variance in male reproductive success was moderately high, possibly because of a combination of random mating and high variance in post-copulatory reproductive success. These results provide the first data on individual mating behaviour among parasitic nematodes

Enabling posthumous medical data donation: a plea for the ethical utilisation of personal health data

This article argues that personal medical data should be made available for scientific research, by enabling and encouraging individuals to donate their medical records once deceased, in a way similar to how they can already donate organs or bodies. This research is part of a project on posthumous medical data donation developed by the Digital Ethics Lab at the Oxford Internet Institute. Ten arguments are provided to support the need to foster posthumous medical data donation. Two major risks are also identified—harm to others, and lack of control over the use of data—which could follow from unregulated donation of medical data. The argument that record-based medical research should proceed without the need to ask for informed consent is rejected, and it instead a voluntary and participatory approach to using personal medical data should be followed. The analysis concludes by stressing the need to develop an ethical code for data donation to minimise the risks providing five foundational principles for ethical medical data donation; and suggesting a draft for such a code

Mixing of rhyolite, trachyte and basalt magma erupted from a vertically and laterally zoned reservoir, composite flow P1, Gran Canaria

The 14.1 Ma composite welded ignimbrite P1 (45 km3 DRE) on Gran Canaria is compositionally zoned from a felsic lower part to a basaltic top. It is composed of four component magmas mixed in vertically varying proportions: (1) Na-rhyolite (10 km3) zoned from crystal-poor to highly phyric; (2) a continuously zoned, evolved trachyte to sodic trachyandesite magma group (6 km3); (3) a minor fraction of Na-poor trachyandesite (<1 km3); and (4) nearly aphyric basalt (26 km3) zoned from 4.3 to 5.2 wt% MgO. We distinguish three sites and phases of mixing: (a) Mutual mineral inclusions show that mixing between trachytic and rhyolitic magmas occurred during early stages of their intratelluric crystallization, providing evidence for long-term residence in a common reservoir prior to eruption. This first phase of mixing was retarded by increasing viscosity of the rhyolite magma upon massive anorthoclase precipitation and accumulation. (b) All component magmas probably erupted through a ring-fissure from a common upper-crustal reservoir into which the basalt intruded during eruption. The second phase of mixing occurred during simultaneous withdrawal of magmas from the chamber and ascent through the conduit. The overall withdrawal and mixing pattern evolved in response to pre-eruptive chamber zonation and density and viscosity relationships among the magmas. Minor sectorial variations around the caldera reflect both varying configurations at the conduit entrance and unsteady discharge. (c) During each eruptive pulse, fragmentation and particulate transport in the vent and as pyroclastic flows caused additional mixing by reducing the length scale of heterogeneities. Based on considerations of magma density changes during crystallization, magma temperature constraints, and the pattern of withdrawal during eruption, we propose that eruption tapped the P1 magma chamber during a transient state of concentric zonation, which had resulted from destruction of a formerly layered zonation in order to maintain gravitational equilibrium. Our model of magma chamber zonation at the time of eruption envisages a basal high-density Na-poor trachyandesite layer that was overlain by a central mass of highly phyric rhyolite magma mantled by a sheath of vertically zoned trachyte-trachyandesite magma along the chamber walls. A conventional model of vertically stacked horizontal layers cannot account for the deduced density relationships nor for the withdrawal pattern

Dynamic Switch of Negative Feedback Regulation in Drosophila Akt–TOR Signaling

Akt represents a nodal point between the Insulin receptor and TOR signaling, and its activation by phosphorylation controls cell proliferation, cell size, and metabolism. The activity of Akt must be carefully balanced, as increased Akt signaling is frequently associated with cancer and as insufficient Akt signaling is linked to metabolic disease and diabetes mellitus. Using a genome-wide RNAi screen in Drosophila cells in culture, and in vivo analyses in the third instar wing imaginal disc, we studied the regulatory circuitries that define dAkt activation. We provide evidence that negative feedback regulation of dAkt occurs during normal Drosophila development in vivo. Whereas in cell culture dAkt is regulated by S6 Kinase (S6K)–dependent negative feedback, this feedback inhibition only plays a minor role in vivo. In contrast, dAkt activation under wild-type conditions is defined by feedback inhibition that depends on TOR Complex 1 (TORC1), but is S6K–independent. This feedback inhibition is switched from TORC1 to S6K only in the context of enhanced TORC1 activity, as triggered by mutations in tsc2. These results illustrate how the Akt–TOR pathway dynamically adapts the routing of negative feedback in response to the activity load of its signaling circuit in vivo

A case report and brief review of the literature on bilateral retinal infarction following cardiopulmonary bypass for coronary artery bypass grafting

Postoperative visual loss is a devastating perioperative complication. The commonest aetiologies are anterior ischaemic optic neuropathy (AION), posterior ischaemic optic neuropathy (PION), and central retinal artery occlusion (CRAO). These appear to be related to certain types of operation, most commonly spinal and cardiac bypass procedures; with the rest divided between: major trauma causing excessive blood loss; head/neck and nasal or sinus surgery; major vascular procedures (aortic aneurysm repair, aorto-bifemoral bypass); general surgery; urology; gynaecology; liposuction; liver transplantation and duration of surgery. The non-surgical risk factors are multifactorial: advanced age, prolonged postoperative anaemia, positioning (supine v prone), alteration of venous drainage of the retina, hypertension, smoking, atherosclerosis, hyperlipidaemia, diabetes, hypercoagulability, hypotension, blood loss and large volume resuscitation. Other important cardiac causes are septic emboli from bacterial endocarditis and emboli caused by atrial myxomata. The majority of AION cases occur during CPB followed by head/neck surgery and prone spine surgery. CPB is used to allow coronary artery bypass grafting on a motionless heart. It has many side-effects and complications associated with its use and we report here a case of bilateral retinal infarction during routine coronary artery bypass grafting in a young male patient with multiple risk factors for developing this complication despite steps to minimise its occurrence

Streaming histogram sketching for rapid microbiome analytics

Background: The growth in publically available microbiome data in recent years has yielded an invaluable resource for genomic research, allowing for the design of new studies, augmentation of novel datasets and reanalysis of published works. This vast amount of microbiome data, as well as the widespread proliferation of microbiome research and the looming era of clinical metagenomics, means there is an urgent need to develop analytics that can process huge amounts of data in a short amount of time. To address this need, we propose a new method for the compact representation of microbiome sequencing data using similarity-preserving sketches of streaming k-mer spectra. These sketches allow for dissimilarity estimation, rapid microbiome catalogue searching and classification of microbiome samples in near real time. Results: We apply streaming histogram sketching to microbiome samples as a form of dimensionality reduction, creating a compressed ‘histosketch’ that can efficiently represent microbiome k-mer spectra. Using public microbiome datasets, we show that histosketches can be clustered by sample type using the pairwise Jaccard similarity estimation, consequently allowing for rapid microbiome similarity searches via a locality sensitive hashing indexing scheme. Furthermore, we use a ‘real life’ example to show that histosketches can train machine learning classifiers to accurately label microbiome samples. Specifically, using a collection of 108 novel microbiome samples from a cohort of premature neonates, we trained and tested a random forest classifier that could accurately predict whether the neonate had received antibiotic treatment (97% accuracy, 96% precision) and could subsequently be used to classify microbiome data streams in less than 3 s. Conclusions: Our method offers a new approach to rapidly process microbiome data streams, allowing samples to be rapidly clustered, indexed and classified. We also provide our implementation, Histosketching Using Little K-mers (HULK), which can histosketch a typical 2 GB microbiome in 50 s on a standard laptop using four cores, with the sketch occupying 3000 bytes of disk space

Clinical risk stratification of paediatric renal transplant recipients using C1q and C3d fixing of de novo donor-specific antibodies

Introduction: We have previously shown that children who developed de novo donor-specific human leukocyte antigen (HLA) antibodies (DSA) had greater decline in allograft function. We hypothesised that patients with complement-activating DSA would have poorer renal allograft outcomes. Methods: A total of 75 children developed DSA in the original study. The first positive DSA sample was subsequently tested for C1q and C3d fixing. The primary event was defined as 50% reduction from baseline estimated glomerular filtration rate and was analysed using the Kaplan–Meier estimator. Results: Of 65 patients tested, 32 (49%) and 23 (35%) tested positive for C1q and C3d fixing, respectively. Of the 32 C1q-positive (c1q+) patients, 13 (41%) did not show concomitant C3d fixing. The mean fluorescence intensity values of the original immunoglobulin G DSA correlated poorly with complement-fixing positivity (C1q: adjusted R2 0.072; C3d: adjusted R2 0.11; p < 0.05). C1q+ antibodies were associated with acute tubulitis [0.75 ± 0.18 (C1q+) vs. 0.25 ± 0.08 (C1q−) episodes per patient (mean ± standard error of the mean; p < 0.05] but not with worse long-term renal allograft dysfunction (median time to primary event 5.9 (C1q+) vs. 6.4 (C1q−) years; hazard ratio (HR) 0.74; 95% confidence ratio (CI) 0.30–1.81; p = 0.58]. C3d-positive (C3d+) antibodies were associated with positive C4d histological staining [47% (C3d+) vs. 20% (C3d−); p = 0.04] and with significantly worse long-term allograft dysfunction [median time to primary event: 5.6 (C3d+) vs. 6.5 (C3d−) years; HR 0.38; 95% CI 0.15–0.97; p = 0.04]. Conclusion: Assessment of C3d fixing as part of prospective HLA monitoring can potentially aid stratification of patients at the highest risk of long-term renal allograft dysfunction