Fecal Coliform Concentrations in the Upper Cohansey River Watershed Predicted by Air Temperature, Discharge, and Land Use

The Upper Cohansey River Watershed in southwestern New Jersey has a history of being affected by fecal coliform bacteria (FC). A study was undertaken to investigate the environmental factors associated with FC concentration. For 44% of samples taken throughout the watershed in 2012–2013, FC concentration exceeded the benchmark value. FC levels were related to air temperature, river discharge, and land use in stream buffers. Human sources of FC had been eliminated following research results published in 2009. Results of the study reported in this article suggest the need to further investigate wildlife sources of FC and to implement additional mitigation actions

Flow-Diversion Treatment of Unruptured Saccular Anterior Communicating Artery Aneurysms: A Systematic Review and Meta-Analysis

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No downregulation of immune function during breeding in two year-round breeding bird species in an equatorial East African environment

Some equatorial environments exhibit substantial within-location variation in environmental conditions throughout the year and yet have year-round breeding birds. This implies that breeding in such systems are potentially unrelated to the variable environmental conditions. By breeding not being influenced by environmental conditions, we become sure that any differences in immune function between breeding and non-breeding birds do not result from environmental variation, therefore allowing for exclusion of the confounding effect of variation in environmental conditions. This create a unique opportunity to test if immune function is down-regulated during reproduction compared to non-breeding periods. We compared the immune function of sympatric male and female chick-feeding and non-breeding red-capped Calandrella cinerea and rufous-naped larks Mirafra africana in equatorial East Africa. These closely-related species occupy different niches and have different breeding strategies in the same grassland habitat. Red-capped larks prefer areas with short grass or almost bare ground, and breed during low rainfall periods. Rufous-naped larks prefer areas of tall grass and scattered shrubs and breed during high rainfall. We measured the following immune indices: nitric oxide, haptoglobin, agglutination and lysis, and measured total monthly rain, monthly average minimum (T-min) and maximum (T-max) temperatures. Contrary to our predictions, we found no down-regulation of immune function during breeding; breeding birds had higher nitric oxide than non-breeding ones in both species, while the other three immune indices did not differ between breeding phases. Red-capped larks had higher nitric oxide concentrations than Rufous-naped larks, which in turn had higher haptoglobin levels than red-capped larks. T-max was higher during breeding than during non-breeding for red-capped larks only, suggesting potential confounding effect of T-max on the comparison of immune function between breeding and non-breeding birds for this species. Overall, we conclude that in the two year-round breeding equatorial larks, immune function is not down-regulated during breeding

Development of machine learning models to prognosticate chronic shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage

Background: Shunt-dependent hydrocephalus significantly complicates subarachnoid hemorrhage (SAH), and reliable prognosis methods have been sought in recent years to reduce morbidity and costs associated with delayed treatment or neglected onset. Machine learning (ML) defines modern data analysis techniques allowing accurate subject-based risk stratifications. We aimed at developing and testing different ML models to predict shunt-dependent hydrocephalus after aneurysmal SAH. Methods: We consulted electronic records of patients with aneurysmal SAH treated at our institution between January 2013 and March 2019. We selected variables for the models according to the results of the previous works on this topic. We trained and tested four ML algorithms on three datasets: one containing binary variables, one considering variables associated with shunt-dependency after an explorative analysis, and one including all variables. For each model, we calculated AUROC, specificity, sensitivity, accuracy, PPV, and also, on the validation set, the NPV and the Matthews correlation coefficient (ϕ). Results: Three hundred eighty-six patients were included. Fifty patients (12.9%) developed shunt-dependency after a mean follow-up of 19.7 (± 12.6) months. Complete information was retrieved for 32 variables, used to train the models. The best models were selected based on the performances on the validation set and were achieved with a distributed random forest model considering 21 variables, with a ϕ = 0.59, AUC = 0.88; sensitivity and specificity of 0.73 (C.I.: 0.39–0.94) and 0.92 (C.I.: 0.84–0.97), respectively; PPV = 0.59 (0.38–0.77); and NPV = 0.96 (0.90–0.98). Accuracy was 0.90 (0.82–0.95). Conclusions: Machine learning prognostic models allow accurate predictions with a large number of variables and a more subject-oriented prognosis. We identified a single best distributed random forest model, with an excellent prognostic capacity (ϕ = 0.58), which could be especially helpful in identifying low-risk patients for shunt-dependency

Mechanical thrombectomy in patients with proximal occlusions and low NIHSS: Results from a large prospective registry

Background: Mechanical thrombectomy is now standard of care for treatment of acute ischemic stroke secondary to large vessel occlusion in the setting of high NIHSS. We analysed a large nationwide registry focusing on patients with large vessel occlusion and low NIHSS on admission to evaluate the efficacy and safety of thrombectomy in this patient population Methods: 2826 patients treated with mechanical thrombectomy were included in a multicentre registry from January 1, 2011 to December 31, 2015. We included patients with large vessel occlusion and NIHSS ≤ 6 on admission. Baseline characteristics, imaging, clinical outcome, procedure adverse events and positive and negative outcome predictors were analysed. Results: 134 patients were included. 90/134 had an anterior circulation and 44 a posterior circulation stroke. One patient died before treatment. Successful revascularization (mTICI 2b-3) was achieved in 73.7% (98/133) of the patients. Intraprocedural adverse event was observed in 3% (4/133) of cases. Symptomatic intracranial haemorrhage rate was 5.3% (7/133). At three months, 70.9% (95/134) of the patients had mRS score 0-2, 15.7% (21/134) mRS 3-5 and 13.4% (18/134) mRS 6. Age and successful recanalization were significant predictors of a good clinical outcome on both univariate (p= 0.005 and p=0.007) and multivariable (p=0.0018 and p=0.009 [nat log]) analysis. Absence of vessel recanalization and symptomatic intracranial hemorrhage were independent predictors of poor outcome (p=0.021). Conclusions: Our study suggests that patients with large vessel occlusion and low NIHSS score on admission can benefit from mechanical thrombectomy. Randomized trials are warranted

Anion exchange membrane soil nitrate predicts turfgrass color and yield.

Desirable nitrogen (N) management practices for turfgrass supply sufficient N for high quality turf while limiting excess soil N. Previous studies suggested the potential of anion exchange membranes (AEMs) for predicting turfgrass color, quality, or yield. However, these studies suggested a wide range of critical soil nitrate-nitrogen (NO3-N) values across sample dates. A field experiment, in randomized complete block design with treatments consisting of nine N application rates, was conducted on a mixed species cool-season turfgrass lawn across two growing seasons. Every 2 wk from May to October, turfgrass color was assessed with three different reflectance meters, and soil NO3-N was measured with in situ AEMs. Cate-Nelson models were developed comparing relative reflectance value and yield to AEM desorbed soil NO3-N pooled across all sample dates. These models predicted critical AEM soil NO3-N values from 0. 45 to 1.4 micro g cm-2 d-1. Turf had a low probability of further positive response to AEM soil NO3-N greater than these critical values. These results suggest that soil NO3-N critical values from AEMs may be applicable across sample dates and years and may serve to guide N fertilization to limit excess soil NO3-N

Second Human Case of Cache Valley Virus Disease

We document the second known case of Cache Valley virus disease in a human. Cache Valley virus disease is rarely diagnosed in North America, in part because laboratories rarely test for it. Its true incidence, effect on public health, and full clinical spectrum remain to be determined

Range area matters, and so does spatial configuration: predicting conservation status in vertebrates

The current rapid loss of biodiversity globally calls for improved tools to predict conservation status. Conservation status varies among taxa and is influenced by intrinsic species’ traits and extrinsic factors. Among these predictors, the most consistently recognized and widely available is geographic range area. However, ranges of equal area can have diverse spatial configurations that reflect variation in threatening processes and species’ characteristics (e.g., dispersal ability), and can affect local and regional population dynamics. The aim of this study is to assess if and how the spatial configuration of a species’ range relates to its conservation status. We obtained range maps and two descriptors of conservation status: extinction risk and population trend, from the IUCN for 11,052 species of amphibians, non-marine birds, and terrestrial mammals distributed across the World. We characterized spatial configuration using descriptors of shape and fragmentation (fragment number and size heterogeneity) and used regression analysis to evaluate their role in explaining current extinction risk and population trend. The most important predictor of conservation status was range area, but our analyses also identified shape and fragmentation as valuable predictors. We detected complex relationships, revealed by multiple interaction terms, e.g. more circular shapes were negatively correlated with population trend, and heterogeneity was positively correlated with extinction risk for small range areas but negatively for bigger ranges. Considering descriptors of spatial configuration beyond size improves our understanding of conservation status among vertebrates. The metrics we propose are relatively easy to define (although values can be sensitive to data quality), and unlike other correlates of status, like species’ traits, are readily available for many species (all of those with range maps). We argue that considering spatial configuration predictors is a straightforward way to improve our capacity to predict conservation status and thus, can be useful to promote more effective conservation