Development of species-specific primers for rapid identification by PCR of the ecologically important pathogen Fusarium keratoplasticum from isolated and environmental samples

The genus Fusarium contains many fungal species known to be pathogenic to animals and plants alike. One species complex within this genus, the Fusarium solani species complex (FSSC), is of particular concern due to its high numbers of pathogenic members. FSSC members are known to contribute significantly to plant, human and other animal fungal disease. One member of the FSSC, Fusarium keratoplasticum, is of particular ecological concern and has been implicated in low hatching success of endangered sea turtle eggs, as well as contribute to human and other animal Fusarium pathogenesis. Species-specific primers for molecular identification of F. keratoplasticum currently do not exist to our knowledge, making rapid identification, tracking and quantitation of this pathogenic fungus difficult. The objective of this study was to develop primers specific to F. keratoplasticum that could be applied to DNA from isolated cultures as well as total (mixed) DNA from environmental samples. RPB2 sequence from 109 Fusarium isolates was aligned and analysed to determine nucleotide polymorphisms specific to F. keratoplasticum useful for primer design. A set of primers were generated and found to be effective for identification of F. keratoplasticum from total DNA extracted from sand surrounding sea turtle nesting sites.     

The Orthocladiinae (Diptera: Chironomidae) of India genus Cricotopus van der Wulp

This is the eleventh part of our series of studies on Orthocladiinae from India. Two new species of the genus Cricotopus, C. albipes and C. tenuisetosus are described in this paper.     

Impact of High Deductible Health Plans on Diabetes Care Quality and Outcomes: Systematic Review

ObjectiveTo provide a review of the impact of high deductible health plans (HDHPs) on the utilizations of services required for optimal management of diabetes and subsequent health outcomes.MethodsSystematic literature review of studies published between January 1, 2000, and May 7, 2021, was conducted that examined the impact of HDHP on diabetes monitoring (eg, recommended laboratory and surveillance testing), routine care (eg, ambulatory appointments), medication management (eg, medication initiation, adherence), and acute health care utilization (eg, emergency department visits, hospitalizations, incident complications).ResultsOf the 303 reviewed articles, 8 were relevant. These studies demonstrated that HDHPs lower spending at the expense of reduced high-value diabetes monitoring, routine care, and medication adherence, potentially contributing to the observed increases in acute health care utilization. Additionally, patient out-of-pocket costs for recommended screenings doubled, and total health care expenditures increased by 49.4% for HDHP enrollees compared with enrollees in traditional health plans. Reductions in disease monitoring and routine care and increases in acute health care utilization were greatest in lower-income patients. None of the studies examined the impact of HDHPs on access to diabetes self-management education, technology use, or glycemic control.ConclusionAlthough HDHPs reduce some health care utilization and costs, they appear to do so at the expense of limiting high-value care and medication adherence. Policymakers, providers, and payers should be more cognizant of the potential for negative consequences of HDHPs on patients’ health.     

An Extreme Value Analysis of Pollutant Concentrations in Surface Soils Due to Atmospheric Deposition

Risk assessments often rely on deterministic models using long-term averages or “steady-state” values of input variables. Such models do not provide the information needed to estimate acute exposures. This study uses extreme value theory to examine the frequency and magnitude of daily pollutant concentrations in surface soils predicted at six U.S. locations. Concentrations are predicted using a deposition-leaching model and 50 years of historical precipitation data. A stochastic model also is used to generate 1000 years of precipitation data as modeling inputs for each location. The annual maximum concentrations at each site are fitted to a Gumbel type I distribution to estimate occurrence probability. For soluble pollutants, the predicted concentration varied substantially with precipitation, and the maximum daily concentrations exceeded annual averages by 4 to 8 times. Observed and synthetic precipitation data produced similar results at most study locations, though the synthetic data provided a slightly better fit to the Gumbel type I distribution. The precipitation model allows the generation of representative precipitation data that extend limited historical records. The extreme value analysis facilitates the evaluation of maximum pollutant concentrations, return periods, and other statistics that are important in evaluating acute exposures.     

Flood Risk Analysis Based on Information Diffusion Theory

Due to the fact that the flood data series of small drainage basins is relatively short, available data are often not sufficient for flood risk analysis. This presents the problem of risk analysis using very small data samples. One method that can be applied is to regard the available small samples as fuzzy information and optimize them using information diffusion technology to yield analytical results with greater reliability. In this article a risk analysis method based on information diffusion theory is applied to create a new flood risk analysis model. Application of the model is illustrated taking the Jinhuajiang and Qujiang drainage basins as examples. This is a new attempt at applying information diffusion theory in flood risk analysis. Computations based on this analytical flood risk model can yield an estimated flood damage value that is relatively accurate. This study indicates that the aforementioned model exhibits fairly stable analytical results, even when using a small set of sample data. The results also indicate that information diffusion technology is highly capable of extracting useful information and therefore improves system recognition accuracy. This method can be easily applied and the analytical results produced are easy to understand. Results are accurate enough to act as a guide in disaster situations.     

In Pursuit of Safety: One-Hundred Years of Toxicological Risk Assessment

The publication in 1962 of Rachel Carson's Silent Spring marks the mid-point in a century that saw, in its first half, the emergence of public health concerns related to human exposures to chemicals, and, in its second half, the emergence of public policies to deal with those concerns. Those policies made it imperative that the scientific community come to grips with the problem of identifying exposure levels not likely to cause harm. This problem was not significantly discussed within the scientific community until the 1950s, and well-described methods for practical solutions to it did not appear until the 1970s. An important report from the National Academy of Sciences, published in 1983 (Risk Assessment in the Federal Government), provided an analysis of these emerging methods, and recommended a useful framework for the assessment and management of risk. This framework remains central to public health and regulatory decision-making. A high-level perspective is offered on events leading to and following the 1983 report. The article describes early thinking about chemical toxicity and the scientific path that thinking followed through the 20th century, and to the present.     

Predator detection and avoidance by starlings under differing scenarios of predation risk

Practically all animals must find food while avoiding predators.An individual's perception of predation risk may depend on manyfactors, such as distance to refuge and group size, but it isunclear whether individuals respond to different factors ina similar manner. We tested whether flocks of foraging starlingsresponded in the same way to an increased perception of predationrisk by assessing three factors: (1) neighbor distances, (2)habitat obstruction, and (3) recent exposure to a predator.We found that in all three scenarios of increased risk, starlingsreduced their interscan intervals (food-searching bouts), whichincreased the frequency of their vigilance periods. We thenexamined how one of these factors, habitat obstruction, affectedescape speed by simulating an attack with a model predator.Starlings were slower to respond in visually obstructed habitats(long grass swards) and slower when they had their head downin obstructed habitats than when they had their head down inopen habitats. In addition, reaction times were quicker whenstarlings could employ their peripheral fields of vision. Ourresults demonstrate that different sources of increased riskcan generate similar behavioral responses within a species.The degree of visibility in the physical and social environmentaffects both the actual and perceived risk of predation.     

Rapid atraumatic sex identification of developmental day 14–16 mice

Abstract

Embryonic mice have been used widely to study organ development. Days 14–16 are critical for sex organ development and differentiation in mice. Current methods for sex identification are limited. Even the simplest polymerase chain reaction method may injure the embryo. We determined that morphologic analysis of embryonic mammary anlagen could be used for rapid atraumatic sex identification of day 14–16 mice. The accuracy of our method was verified by molecular and anatomical approaches.     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.