A meta-BACI approach forevaluating management intervention on chronic wasting disease in mule deer

Advances in acquiring and analyzing the spatial attributes of data have greatlyenhanced the potential utility of wildlife disease surveillance data for addressing problems ofecological or economic importance. We present an approach for using wildlife diseasesurveillance data to identify areas for (or of ) intervention, to spatially delineate pairedtreatment and control areas, and then to analyze these nonrandomly selected sites in a meta-analysis framework via before–after–control–impact (BACI) estimates of effect size. We applythese methods to evaluate the effectiveness of attempts to reduce chronic wasting disease(CWD) prevalence through intensive localized culling of mule deer (Odocoileus hemionus)innorth-central Colorado, USA. Areas where surveillance data revealed high prevalence or caseclusters were targeted by state wildlife management agency personnel for focal scale (onaverage ,17 km2) culling, primarily via agency sharpshooters. Each area of sustained cullingthat we could also identify as unique by cluster analysis was considered a potential treatmentarea. Treatment areas, along with spatially paired control areas that we constructed post hocin a case-control design (collectively called ‘‘management evaluation sites’’), were thendelineated using home range estimators. Using meta-BACI analysis of CWD prevalence datafor all management evaluation sites, the mean effect size (change of prevalence on treatmentareas minus change in prevalence on their paired control areas) was 0.03 (SE ¼ 0.03); meaneffect size on treatment areas was not greater than on paired control areas. Excluding cullsamples from prevalence estimates or allowing for an equal or greater two-year lag in systemresponses to management did not change this outcome. We concluded that managementbenefits were not evident, although whether this represented true ineffectiveness or was a resultof lack of data or insufficient duration of treatment could not be discerned. Based on ourobservations, we offer recommendations for designing a management experiment with 80%power to detect a 0.10 drop in prevalence over a 6–12-year period

Elk Contact Patterns and Potential Disease Transmission

Understanding the drivers of contact rates among individuals is critical to understanding disease dynamics and implementing targeted control measures. We studied the interaction patterns of 149 female elk (Cervus elaphus) distributed across five different regions of western Wyoming over three years, defining a contact as an approach within one body length (~2m). Using hierarchical models that account for correlations within individuals, pairs and groups, we found that pairwise contact rates within a group declined by a factor of three as group sizes increased 30-fold. Meanwhile, per capita contact rates increased with group size due to the increasing number of potential pairs. We found similar patterns for the duration of contacts. Supplemental feeding of elk had a limited impact on pairwise interaction rates and durations, but increased per capita rates more than two times higher. Variation in contact patterns were driven more by environmental factors such as group size than either individual or pairwise differences. Female elk in this region fall between the expectation of contact rates that linearly increase with group size (as assumed by pseudo-mass action models of disease transmission) or are constant with changes in group size (as assumed by frequency dependent transmission models). Our statistical approach decomposes the variation in contact rate into individual, dyadic, and environmental effects, which provides insight into those factors that are important for effective disease control programs

Electrocardiographic Deep Learning for Predicting Post-Procedural Mortality

Background. Pre-operative risk assessments used in clinical practice are limited in their ability to identify risk for post-operative mortality. We hypothesize that electrocardiograms contain hidden risk markers that can help prognosticate post-operative mortality. Methods. In a derivation cohort of 45,969 pre-operative patients (age 59+- 19 years, 55 percent women), a deep learning algorithm was developed to leverage waveform signals from pre-operative ECGs to discriminate post-operative mortality. Model performance was assessed in a holdout internal test dataset and in two external hospital cohorts and compared with the Revised Cardiac Risk Index (RCRI) score. Results. In the derivation cohort, there were 1,452 deaths. The algorithm discriminates mortality with an AUC of 0.83 (95% CI 0.79-0.87) surpassing the discrimination of the RCRI score with an AUC of 0.67 (CI 0.61-0.72) in the held out test cohort. Patients determined to be high risk by the deep learning model's risk prediction had an unadjusted odds ratio (OR) of 8.83 (5.57-13.20) for post-operative mortality as compared to an unadjusted OR of 2.08 (CI 0.77-3.50) for post-operative mortality for RCRI greater than 2. The deep learning algorithm performed similarly for patients undergoing cardiac surgery with an AUC of 0.85 (CI 0.77-0.92), non-cardiac surgery with an AUC of 0.83 (0.79-0.88), and catherization or endoscopy suite procedures with an AUC of 0.76 (0.72-0.81). The algorithm similarly discriminated risk for mortality in two separate external validation cohorts from independent healthcare systems with AUCs of 0.79 (0.75-0.83) and 0.75 (0.74-0.76) respectively. Conclusion. The findings demonstrate how a novel deep learning algorithm, applied to pre-operative ECGs, can improve discrimination of post-operative mortality

Attenuated and Protease-Profile Modified Sendai Virus Vectors as a New Tool for Virotherapy of Solid Tumors

Peer reviewe

Glucose transporter-1 deficiency syndrome: the expanding clinical and genetic spectrum of a treatable disorder

Glucose transporter-1 deficiency syndrome is caused by mutations in the SLC2A1 gene in the majority of patients and results in impaired glucose transport into the brain. From 2004-2008, 132 requests for mutational analysis of the SLC2A1 gene were studied by automated Sanger sequencing and multiplex ligation-dependent probe amplification. Mutations in the SLC2A1 gene were detected in 54 patients (41%) and subsequently in three clinically affected family members. In these 57 patients we identified 49 different mutations, including six multiple exon deletions, six known mutations and 37 novel mutations (13 missense, five nonsense, 13 frame shift, four splice site and two translation initiation mutations). Clinical data were retrospectively collected from referring physicians by means of a questionnaire. Three different phenotypes were recognized: (i) the classical phenotype (84%), subdivided into early-onset (<2 years) (65%) and late-onset (18%); (ii) a non-classical phenotype, with mental retardation and movement disorder, without epilepsy (15%); and (iii) one adult case of glucose transporter-1 deficiency syndrome with minimal symptoms. Recognizing glucose transporter-1 deficiency syndrome is important, since a ketogenic diet was effective in most of the patients with epilepsy (86%) and also reduced movement disorders in 48% of the patients with a classical phenotype and 71% of the patients with a non-classical phenotype. The average delay in diagnosing classical glucose transporter-1 deficiency syndrome was 6.6 years (range 1 month-16 years). Cerebrospinal fluid glucose was below 2.5 mmol/l (range 0.9-2.4 mmol/l) in all patients and cerebrospinal fluid : blood glucose ratio was below 0.50 in all but one patient (range 0.19-0.52). Cerebrospinal fluid lactate was low to normal in all patients. Our relatively large series of 57 patients with glucose transporter-1 deficiency syndrome allowed us to identify correlations between genotype, phenotype and biochemical data. Type of mutation was related to the severity of mental retardation and the presence of complex movement disorders. Cerebrospinal fluid : blood glucose ratio was related to type of mutation and phenotype. In conclusion, a substantial number of the patients with glucose transporter-1 deficiency syndrome do not have epilepsy. Our study demonstrates that a lumbar puncture provides the diagnostic clue to glucose transporter-1 deficiency syndrome and can thereby dramatically reduce diagnostic delay to allow early start of the ketogenic die

ICDP workshop on the Lake Tanganyika Scientific Drilling Project: a late Miocene–present record of climate, rifting, and ecosystem evolution from the world's oldest tropical lake

The Neogene and Quaternary are characterized by enormous changes in global climate and environments, including global cooling and the establishment of northern high-latitude glaciers. These changes reshaped global ecosystems, including the emergence of tropical dry forests and savannahs that are found in Africa today, which in turn may have influenced the evolution of humans and their ancestors. However, despite decades of research we lack long, continuous, well-resolved records of tropical climate, ecosystem changes, and surface processes necessary to understand their interactions and influences on evolutionary processes. Lake Tanganyika, Africa, contains the most continuous, long continental climate record from the mid-Miocene (∼10 Ma) to the present anywhere in the tropics and has long been recognized as a top-priority site for scientific drilling. The lake is surrounded by the Miombo woodlands, part of the largest dry tropical biome on Earth. Lake Tanganyika also harbors incredibly diverse endemic biota and an entirely unexplored deep microbial biosphere, and it provides textbook examples of rift segmentation, fault behavior, and associated surface processes. To evaluate the interdisciplinary scientific opportunities that an ICDP drilling program at Lake Tanganyika could offer, more than 70 scientists representing 12 countries and a variety of scientific disciplines met in Dar es Salaam, Tanzania, in June 2019. The team developed key research objectives in basin evolution, source-to-sink sedimentology, organismal evolution, geomicrobiology, paleoclimatology, paleolimnology, terrestrial paleoecology, paleoanthropology, and geochronology to be addressed through scientific drilling on Lake Tanganyika. They also identified drilling targets and strategies, logistical challenges, and education and capacity building programs to be carried out through the project. Participants concluded that a drilling program at Lake Tanganyika would produce the first continuous Miocene–present record from the tropics, transforming our understanding of global environmental change, the environmental context of human origins in Africa, and providing a detailed window into the dynamics, tempo and mode of biological diversification and adaptive radiations.© Author(s) 2020. This open access article is distributed under the Creative Commons Attribution 4.0 License

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase&nbsp;1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation&nbsp;disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age&nbsp; 6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score&nbsp; 652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc&nbsp;= 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N&nbsp;= 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in&nbsp;Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in&nbsp;Asia&nbsp;and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

Environmental radiation monitoring plan for depleted uranium and beryllium areas, Yuma Proving Ground

This Environmental Radiation Monitoring Plan (ERM) discusses sampling soils, vegetation, and biota for depleted uranium (DU) and beryllium (Be) at Yuma Proving Ground (YPG). The existing ERM plan was used and modified to more adequately assess the potential of DU and Be migration through the YPG ecosystem. The potential pathways for DU and Be migration are discussed and include soil to vegetation, soil to animals, vegetation to animals, animals to animals, and animals to man. Sample collection will show DU deposition and will be used to estimate DU migration. The number of samples from each area varies and depends on if the firing range of interest is currently used for DU testing (GP 17A) or if the range is not used currently for DU testing (GP 20). Twenty to thirty-five individual mammals or lizards will be sampled from each transect. Air samples and samples of dust in the air fall will be collected in three locations in the active ranges. Thirty to forty-five sediment samples will be collected from different locations in the arroys near the impact areas. DU and Be sampling in the Hard Impact and Soft Impact areas changed only slightly from the existing ERM. The modifications are changes in sample locations, addition of two sediment transport locations, addition of vegetation samples, mammal samples, and air sampling from three to five positions on the impact areas. Analysis of samples for DU or total U by inductively-coupled mass spectroscopy (ICP/MS), cc spectroscopy, neutron activation analysis (NAA), and kinetic phosphorimetric analysis (KPA) are discussed, and analysis for Be by ICP/MS are recommended. Acquiring total U (no isotope data) from a large number of samples and analysis of those samples with relatively high total U concentrations results in fewer isotopic identifications but more information on U distribution. From previous studies, total U concentrations greater than about 3 times natural background are usually DU by isotopic confirmation